JP3831390B2 - Color signal selection device, color signal interpolation device, color signal generation device, encircling point selection method, and color conversion table creation method - Google Patents

Description

  The present invention relates to a color signal selection device, a color signal generation device, a color signal interpolation device, an encircling point selection method, and a color conversion table creation method, and in particular, input from irregularly distributed points in space. It is suitable for application when selecting a point surrounding the point.

  In recent years, full-colorization has rapidly progressed in printers, facsimiles, and the like, and there is a demand for sharing color images between different devices. However, when a color image is to be shared between different devices, the color reproducibility is also different for different devices, so the color of the image obtained on the transmission side is different from the color of the image obtained on the reception side. appear.

  For example, printers and scanners handle colors in the form of color signals sent to devices such as CMY signals and RGB signals, respectively. That is, in a printer in which the minimum value of the output color signal is 0 and the maximum value of the output color signal is 255, all output colors are expressed by combinations of the CMY signal values ranging from 0 to 255. . In this case, even if CMY signals having the same value are input, the color to be printed differs depending on the printer model. Therefore, the color expression method based on the CMY signals can be said to be a color representation method dependent on the device. .

  Therefore, conventionally, the color reproducibility between different devices has been made consistent by representing the color signal represented in a device-dependent representation format in an intermediate representation format independent of the device. Yes.

  For example, as a method of expressing a color that represents an absolute color that does not depend on a device, there is a method of expressing a color using an L * a * b * signal, an XYZ signal, or the like. Since the colors represented in these formats are uniquely defined, they can be used as an intermediate color expression method when color conversion is performed between the color spaces of different devices.

  Specifically, the image expressed by the RGB signal input from the scanner is converted into an image expressed by the L * a * b * signal, and this L * a * b * signal is converted into a CMY signal. Then output to the printer. For this reason, if conversion of the expression format of these color signals is accurately performed, colors can be matched between devices.

  In order to convert the representation format of the color signal, it is necessary to convert the color signal value represented in each format into the color signal value of another format. As a method of converting the value of the color signal, there is a method of using a color conversion table showing the correspondence of colors in each color space. In the color signal conversion method using the color conversion table, when converting a color signal registered in the color conversion table into a color signal of another format, conversion is performed using the correspondence relationship registered in the color conversion table. To do. When converting a color signal not registered in the color conversion table into a color signal of another format, select a color signal near the color signal to be converted from the color signals registered in the color conversion table. To do. Then, by interpolating using these selected color signals, the color signal to be converted is converted.

  Here, there are two types of color conversion tables: a rule table and an irregular table. In the rule table, color signals to be converted are regularly distributed in the color space, and in the irregular table, color signals to be converted are irregularly distributed in the color space.

  When color conversion is performed using a rule table, even if a color signal not registered in the color conversion table is input as a conversion target, it is converted from the color signals registered in the color conversion table. The color signal surrounding the color signal can be easily selected.

  Since these selected color signals are distributed at grid points in the color space, conversion of the color signals to be converted is relatively easy by tetrahedral interpolation, triangular prism interpolation, cube interpolation, or the like. Is possible.

  On the other hand, when color conversion is performed using an irregular table, when a color signal not registered in the color conversion table is input as a conversion target, conversion is performed from among the color signals registered in the color conversion table. Even if a color signal in the vicinity of the target color signal is selected, the color signal to be converted is not necessarily surrounded by the selected color signal. For this reason, even when interpolation is performed using a color signal near the color signal to be converted, the accuracy of the interpolation may not be sufficient.

  As a method for selecting a color for performing an interpolation operation by color conversion and a method for converting the configuration of the color conversion table into a table that can be easily used when executing color conversion, for example, Japanese Patent Laid-Open No. 7-1990. There is one described in Japanese Patent No. 95431.

  Here, a method of performing interpolation by using data that is not distributed to grid points in the color space is shown. That is, a method for selecting a color when performing color conversion using an irregular table is described.

FIG. 37 is a flowchart showing this conventional color selection method.
In FIG. 37, first, k points x1 to xk closest to the point x to be interpolated are selected (step S181).

  Next, it is checked whether or not the point x to be interpolated is surrounded by the selected k points x1 to xk (step S182). If the point x to be interpolated is not surrounded by the selected k points x1 to xk (step S183), the next closest point is selected (step S184), and the point to be interpolated is selected. This process continues until a point surrounding x is found. When points surrounding the point x to be interpolated are selected, interpolation is performed by using these selected points (step S185).

Furthermore, in Patent Document 1, by using convex interpolation, a color conversion table (irregular table) in which color signals are not distributed at lattice points is converted into a color conversion table (rule table) in which color signals are distributed at lattice points. It is also mentioned how to do. In this method, a color signal having a regular distribution is created using convex interpolation, and the created color signal is registered in a rule table.
JP 7-95431 A

  However, in the conventional color signal selection method, when the point x to be interpolated is not surrounded by the selected k points x1 to xk, the point x to be interpolated is surrounded to perform data selection again. It was necessary to repeat selection of data to find a point to do. For this reason, there is a problem that the processing time for selecting a point surrounding the point x to be interpolated becomes long.

  In addition, since it takes time to select the surrounding color signal and the processing speed of the color conversion decreases, there is a problem that the processing speed similarly decreases even when used for conversion from an irregular table to a rule table. .

  Furthermore, when the color signal registered in the rule table is generated from the irregular table by interpolation, there is a problem that the color signal cannot be generated outside the range surrounded by the color signal registered in the irregular table. .

Accordingly, a first object of the present invention is to make it possible to select at high speed a point that surrounds an input point from among points that are irregularly distributed in space.
The second object of the present invention is to make it possible to generate a color signal of a rule table from an irregular table without omission.

  In order to solve the above-described problem, according to the present invention, a color space dividing unit that divides a color space to which the first color signal belongs with reference to the input first color signal, and a divided color Color signal selection means for selecting the second color signal from the space.

  As a result, even when the second color signal is irregularly distributed in the color space, the selection of the second color signal surrounding the first color signal does not fail, and the first color signal does not fail. Since the selection of the color signal that does not surround the color signal is prevented and the selection of the second color signal can be eliminated, the second color signal that surrounds the first color signal can be selected at high speed. It becomes possible to do.

In addition, according to one aspect of the present invention, rotation conversion is performed so that the second color signal is in a predetermined region.
As a result, when the second color signal surrounding the first color signal is selected, the number of the second color signals can be reduced as much as possible, and the interpolation calculation can be easily performed. .

According to one aspect of the present invention, the second color signal is selected based on the magnitude relationship between the value of each component of the first color signal and the value of each component of the second color signal. ing.
As a result, the second color signal surrounding the first color signal is reliably selected only by comparing the value of each component of the first color signal and the value of each component of the second color signal. Therefore, the second color signal surrounding the first color signal can be selected simply by performing a simple calculation.

According to one aspect of the present invention, a color signal having the shortest distance from the first color signal is selected from the divided color space as the second color signal.
Accordingly, it is possible to prevent the color signal at a point away from the first color signal from being used for the interpolation calculation, and to perform the interpolation calculation of the first color signal using the second color signal with high accuracy. It becomes possible.

  According to one aspect of the present invention, the shortest color signal whose distance from the first color signal is a predetermined value or more is selected from the divided color space as the second color signal. As a result, only a color signal within a limited narrow range is selected, so that it is possible to prevent deviation from occurring in the range of color signals that can be generated by interpolation, and color reproduction in the color space. It is possible to eliminate missing color signals that can be generated within the range.

  Further, according to one aspect of the present invention, the color space dividing unit that divides the first color space based on the input first color signal, and the second color signal from the divided first color space. And a color signal calculation means for calculating the conversion result of the first color signal to the second color space based on the conversion result of the second color signal to the second color space. And.

  Thus, even when the second color signal is irregularly distributed on the first color space, by taking out the second color signal one by one from the divided first color space, Since the first color signal can be surely surrounded by the second color signal, and the second color signal necessary for interpolation of the first color signal can be quickly selected. Signal interpolation can be performed at high speed.

Further, according to one aspect of the present invention, the first color space is divided on the basis of the value of the grid point on the first color space.
This makes it possible to regularly generate interpolation points in the first color space, eliminate the deviation in the distribution of color signals in the first color space, and change the color in the first color space. The signal distribution can be made uniform.

  Further, according to one aspect of the present invention, the color space dividing unit that divides the first color space based on the input first color signal, and the second color signal from the divided first color space. And a conversion result for the third color signal surrounded by the second color signal is calculated based on the color signal selection means for selecting the second color signal and the conversion result of the second color signal to the second color space. Color signal calculating means.

  Accordingly, the third color signal to be interpolated in the first color space can be different from the first color signal to be the reference point for division in the first color space. Even when a different color signal is input as the third color signal, it is possible to set a common reference point for dividing the color space, and therefore, within the same range surrounded by the second color signal. For the third color signals having different values, the second color signal can be selected at once.

Further, according to one aspect of the present invention, the first color space is divided on the basis of the value of the grid point on the first color space.
This makes it possible to set the reference points for selection of the second color signal at equal intervals on the first color space, and to select the second color signal on the first color space. It becomes possible to carry out regularly.

Further, according to one aspect of the present invention, the lattice spacing of lattice points is changed based on the density of the color signal distributed in the first color space.
This makes it possible to prevent the same second color signal from being selected for different lattice points when the second color signal is selected on the basis of the lattice point. Since it becomes possible to reduce the overlap of the range surrounded by the signal, it is possible to efficiently generate a new interpolation point on the first color space.

Further, according to one aspect of the present invention, a color signal distributed in the first color space is input as the first color signal.
As a result, the range surrounded by the second color signal selected on the basis of the first color signal can be set without any gap in the entire range of the color signal distributed in the first color space. This makes it possible to prevent missing color signals that can be generated within the color reproduction range in the color space. Note that the color signal distributed in the first color space is, for example, a value registered in the color conversion table.

Further, according to one aspect of the present invention, the value of the grid point on the first color space is set as the third color signal.
As a result, even when the third color signal to be interpolated in the first color space is different from the first color signal to be the reference point for division in the first color space, the first color signal is different. It becomes possible to obtain color signals of lattice points in the color space.

  According to one aspect of the present invention, the color signal input means for inputting the first color signal belonging to the first color space and the color for selecting the second color signal surrounding the first color signal. Signal selection means; correspondence relation acquisition means for acquiring a correspondence relation between the second color signal and the third color signal belonging to the second color space; and the second color selected by the color signal selection means. Weighting factor setting means for setting a weighting factor for the signal, interpolation point generating means for generating an interpolation point within a range surrounded by the second color signal based on the weighting factor, and the weighting factor setting means The weighting factor selection unit that selects the weighting factor of the interpolation point closest to the fourth color signal surrounded by the second color signal from the weighting factor set by the selection by the weighting factor selection unit Applying the weighted factor to the third color signal More, and an interpolation calculating means for calculating a transformation result to the second color space of the fourth color signals.

  As a result, when the second color signal surrounding the first color signal is selected, the number of the second color signals can be reduced as much as possible, and the interpolation calculation can be easily performed. .

According to one aspect of the present invention, the second color signal is selected based on the magnitude relationship between the value of each component of the first color signal and the value of each component of the second color signal. ing.
As a result, the second color signal surrounding the first color signal is reliably selected only by comparing the value of each component of the first color signal and the value of each component of the second color signal. Therefore, the second color signal surrounding the first color signal can be selected simply by performing a simple calculation.

According to one aspect of the present invention, a color signal having the shortest distance from the first color signal is selected from the divided color space as the second color signal.
Accordingly, it is possible to prevent the color signal at a point away from the first color signal from being used for the interpolation calculation, and to perform the interpolation calculation of the first color signal using the second color signal with high accuracy. It becomes possible.

  According to one aspect of the present invention, the shortest color signal whose distance from the first color signal is a predetermined value or more is selected from the divided color space as the second color signal. As a result, only a color signal within a limited narrow range is selected, so that it is possible to prevent deviation from occurring in the range of color signals that can be generated by interpolation, and color reproduction in the color space. It is possible to eliminate missing color signals that can be generated within the range.

  Further, according to one aspect of the present invention, the color space dividing unit that divides the first color space based on the input first color signal, and the second color signal from the divided first color space. And a color signal calculation means for calculating the conversion result of the first color signal to the second color space based on the conversion result of the second color signal to the second color space. And.

  Thus, even when the second color signal is irregularly distributed on the first color space, by taking out the second color signal one by one from the divided first color space, Since the first color signal can be surely surrounded by the second color signal, and the second color signal necessary for interpolation of the first color signal can be quickly selected. Signal interpolation can be performed at high speed.

Further, according to one aspect of the present invention, the first color space is divided on the basis of the value of the grid point on the first color space.
This makes it possible to regularly generate interpolation points in the first color space, eliminate the deviation in the distribution of color signals in the first color space, and change the color in the first color space. The signal distribution can be made uniform.

  Further, according to one aspect of the present invention, the color space dividing unit that divides the first color space based on the input first color signal, and the second color signal from the divided first color space. And a conversion result for the third color signal surrounded by the second color signal is calculated based on the color signal selection means for selecting the second color signal and the conversion result of the second color signal to the second color space. Color signal calculating means.

  Accordingly, the third color signal to be interpolated in the first color space can be different from the first color signal to be the reference point for division in the first color space. Even when a different color signal is input as the third color signal, it is possible to set a common reference point for dividing the color space, and therefore, within the same range surrounded by the second color signal. For the third color signals having different values, the second color signal can be selected at once.

Further, according to one aspect of the present invention, the first color space is divided on the basis of the value of the grid point on the first color space.
This makes it possible to set the reference points for selection of the second color signal at equal intervals on the first color space, and to select the second color signal on the first color space. It becomes possible to carry out regularly.

Further, according to one aspect of the present invention, the lattice spacing of lattice points is changed based on the density of the color signal distributed in the first color space.
This makes it possible to prevent the same second color signal from being selected for different lattice points when the second color signal is selected on the basis of the lattice point. Since it becomes possible to reduce the overlap of the range surrounded by the signal, it is possible to efficiently generate a new interpolation point on the first color space.

Further, according to one aspect of the present invention, a color signal distributed in the first color space is input as the first color signal.
As a result, the range surrounded by the second color signal selected on the basis of the first color signal can be set without any gap in the entire range of the color signal distributed in the first color space. This makes it possible to prevent missing color signals that can be generated within the color reproduction range in the color space.

Further, according to one aspect of the present invention, the value of the grid point on the first color space is set as the third color signal.
As a result, even when the third color signal to be interpolated in the first color space is different from the first color signal to be the reference point for division in the first color space, the first color signal is different. It becomes possible to obtain color signals of lattice points in the color space.

  According to one aspect of the present invention, the color signal input means for inputting the first color signal belonging to the first color space and the color for selecting the second color signal surrounding the first color signal. Signal selection means; correspondence relation acquisition means for acquiring a correspondence relation between the second color signal and the third color signal belonging to the second color space; and the second color selected by the color signal selection means. Weighting factor setting means for setting a weighting factor for the signal, interpolation point generating means for generating an interpolation point within a range surrounded by the second color signal based on the weighting factor, and the weighting factor setting means The weighting factor selection unit that selects the weighting factor of the interpolation point closest to the fourth color signal surrounded by the second color signal from the weighting factor set by the selection by the weighting factor selection unit Applying the weighted factor to the third color signal More, and an interpolation calculating means for calculating a transformation result to the second color space of the fourth color signals.

  As a result, even when the second color signal is irregularly distributed in the first color space, it is possible to set the weighting coefficient used for the interpolation of the first color space. It is possible to obtain the value of the color signal in the second color space using the weighting coefficient used when obtaining the interpolation point in the first color space, and it is newly given in the first color space. It is possible to obtain a value on the second color space for the color signal.

In addition, according to one aspect of the present invention, the second color signal is selected from the first color space divided on the basis of the first color signal.
Thus, even when the second color signal is irregularly distributed in the first color space, the selection of the second color signal surrounding the first color signal does not fail. Therefore, the second color signal surrounding the first color signal can be selected at high speed, and the interpolation point can be generated at high speed.

Further, according to one aspect of the present invention, the volume when a cube is divided at a predetermined interval is set as a weighting factor when generating an interpolation point.
As a result, even when the second color signal is irregularly distributed in the first color space, an interpolation point can be generated by 8-point interpolation, and the interpolation method is less susceptible to noise. Can be provided.

According to one aspect of the present invention, the interval at which the cube is divided is changed based on the distance between the second color signals or the distance between the third color signals.
This makes it possible to control the interval between the interpolation points on the first color space or the interval between the interpolation points on the second color space, and a range surrounded by the second color signal or the third color signal. Even in the case where the image is distorted, it is possible to generate the interpolation points uniformly in the first color space or the second color space. It is possible to perform signal interpolation.

In addition, according to one aspect of the present invention, when a plurality of fourth color signals are surrounded by the same second color signal, the weighting factors for the fourth color signal are selected collectively. ing.
This eliminates the need to repeat the selection of the same second color signal for a plurality of fourth color signals, and allows the conversion result of the fourth color signal within the same range to be calculated efficiently. Become.

Further, according to one aspect of the present invention, the first color space is a device-dependent color space that depends on a device, and the second color space is an independent color space that does not depend on the device.
Thus, even when color signals are transmitted and received between devices having different color reproducibility, the color reproducibility between the devices can be matched.

Further, according to one aspect of the present invention, the first color space is a CMY space, a CMYK space, or an RGB space, and the second color space is an L * a * b * space or an XYZ space.
As a result, the color signal in the device-dependent color space depending on the device can be converted into the color signal in the independent color space independent of the device.

  Further, according to one aspect of the present invention, the first interpolation point generation means for generating the first interpolation point within the range surrounded by the first color signal distributed in the color space, and the distribution in the color space. A second interpolation point generating means for generating a second interpolation point within a range surrounded by the second color signal, and the first interpolation point or the second interpolation point of the color space. Interpolation point selection means for selecting the one closer to the third color signal, and when the first interpolation point is selected by the interpolation point selection means, the third color signal is used using the first color signal. Interpolating means for performing interpolation of the third color signal using the second color signal when the second interpolation point is selected by the interpolation point selecting means. Yes.

  As a result, as a result of selecting a color signal to be used for interpolation of the third color signal on the basis of a difference from the third color signal, a plurality of color signal candidates to be used for interpolation of the third color signal are obtained. Even in such a case, it is possible to select an optimum color signal to be used for interpolation of the third color signal from among the plurality of color signal candidates.

  According to one aspect of the present invention, the color signal input means for inputting the first color signal belonging to the first color space and the color for selecting the second color signal surrounding the first color signal. And a color signal calculating unit that calculates a conversion result of the third color signal surrounded by the second color signal based on the conversion result of the second color signal into the second color space. And extrapolation means for calculating the conversion result of the fourth color signal outside the range surrounded by the second color signal by extrapolation.

As a result, even when the second color signal is irregularly distributed in the first color space, a new color signal can be generated outside the range surrounded by the second color signal. It becomes.
According to one aspect of the present invention, the second color signal is selected from the first color space divided on the basis of the first color signal.

  Thus, even when the second color signal is irregularly distributed in the first color space, the selection of the second color signal surrounding the first color signal does not fail. Therefore, the second color signal surrounding the first color signal can be selected at high speed, the interpolation point can be generated at high speed, and the generation of the extrapolation point can be accelerated. Therefore, it is possible to efficiently generate a new color signal outside the range surrounded by the color signals distributed in the first color space.

  According to an aspect of the present invention, in the encircling point selection method for selecting three points enclosing the first point in the two-dimensional space, the second point in the vicinity of the first point is selected. A step, rotating the coordinate axis around the first point so that the second point is on the coordinate axis, and selecting one point at a time from areas facing the coordinate axis. .

This makes it possible to reliably select the three points surrounding the first point in the two-dimensional space, and to surround the first point in the two-dimensional space with the minimum number of points. It becomes.
According to another aspect of the present invention, in a surrounding point selection method for selecting four points surrounding a first point in a three-dimensional space, a second point in the vicinity of the first point is selected. A step of rotating the first coordinate axis so that the second point is in a negative region on the first coordinate axis; a third region from the positive region on the first coordinate axis after the rotation; Selecting a point; and the second coordinate axis so that the third point is on a plane composed of the first coordinate axis and the second coordinate axis and is in a negative region of the second coordinate axis. Selecting a fourth point from an area in which the first coordinate axis and the second coordinate axis are negative and the third coordinate axis is 0 or more, and the first coordinate axis and the second coordinate axis Selecting a fifth point from a region where the coordinate axis is negative and the third coordinate axis is negative It is equipped with a.

This makes it possible to reliably select four points that surround the first point in the three-dimensional space, and to surround the first point in the three-dimensional space with a minimum number of points. It becomes.
Further, according to one aspect of the present invention, the first of the first color signal that is irregularly distributed in the first color space and the second color signal that is distributed in the second color space. Determining a correspondence relationship; setting a reference point in the first color space; dividing the first color space at the reference point; and outputting a first color signal from the divided color space. By selecting and interpolating based on the selected first color signal, the first distributed in the grid points of the first color space within the range surrounded by the first color signal. Determining the second correspondence relationship between the third color signal and the fourth color signal distributed in the second color space, and extrapolating the second correspondence relationship, The fifth color signal distributed at the grid points of the first color space outside the range surrounded by the color signals of Obtaining a third correspondence relationship with the sixth color signal distributed in the second color space, and registering the second correspondence relationship and the third correspondence relationship in a color conversion table. And.

  Thus, even when the first color signal is irregularly distributed in the first color space, the first color signal is not failed in selecting the first color signal used for the interpolation calculation. It is possible to generate interpolation points within the range surrounded by, and to generate extrapolation points outside the range surrounded by the first color signal, so as to correspond to the grid points of the first color space. Thus, it is possible to obtain a color signal of the color space, and to efficiently convert the irregular table into the rule table.

According to another aspect of the invention, the reference point is the first color signal.
This makes it possible to select the second color signal based on the first color signal that is irregularly distributed in the first color space, and is surrounded by the second color signal. Since it is possible to set the range of the first color space to the entire range of the color signal distributed in the first color space without any gap, there is no omission in the range of the registered color signal. A color conversion table can be generated.

According to another aspect of the invention, the reference point is the third color signal.
As a result, the second color signal can be selected on the basis of the lattice point of the first color space, and the interpolation points can be regularly generated on the first color space. As a result, it is possible to generate a color conversion table that does not deviate from registered color signals.

According to another aspect of the invention, the reference point is a part of the third color signal.
Thus, since the density of the grid points registered in the color conversion table is larger than the density of the first color signal, the first color signal can be obtained even when different grid points are surrounded by the same first color signal. By reducing the number of reference points that serve as the reference for selection, it is possible to reduce the overlap of the range surrounded by the first color signal, so that the same processing is repeated many times for the same range. It becomes possible to prevent this, and it becomes possible to efficiently convert an irregular table into a rule table.

  According to one aspect of the present invention, in the step of obtaining the second correspondence relationship, a volume when the cube is divided at a predetermined interval is set as a weighting factor for the selected first color signal. A step of generating an interpolation point within a range surrounded by the first color signal based on the weighting factor, and a range surrounded by the first color signal among the set weighting factors Selecting a weighting factor of an interpolation point closest to the third color signal, and calculating the fourth color signal by applying the selected weighting factor to the second color signal. I have.

  Thus, even when the first color signal is irregularly distributed in the first color space, 8-point interpolation can be performed in the first color space, and the first color It is possible to obtain the value of the color signal in the second color space using the weighting coefficient used when obtaining the interpolation point in the space, and to convert the irregular table into the rule table with high accuracy. Become.

  Further, according to one aspect of the present invention, the step of obtaining the third correspondence relationship includes a second step adjacent to the outside of the boundary of the range surrounded by the first color signal on the first color space. Selecting one grid point, selecting a second grid point adjacent to the inside of the first grid point on the first color space, and on the first color space, Selecting a third grid point that is only one inside from the second grid point, and on the second color space corresponding to the second grid point based on the second correspondence relationship Obtaining a first point; obtaining a second point on the second color space corresponding to the third grid point based on the second correspondence; and the second point Obtaining a color signal of a third point that is symmetric with respect to the second point around the first point on a color space; Serial to correspond to the color signals of the first grid point, and a step of registering the color signal of the third point in the color conversion table.

  This makes it possible to generate a point created by extrapolation on a straight line connecting two points used in extrapolation, and the fourth color signal in the vicinity of the sixth color signal generated by extrapolation. Since the sixth color signal can be calculated by a simple calculation using the color signal, it is possible to calculate the color signal outside the range surrounded by the first color signal with high speed and accuracy. Become.

  As described above, according to the present invention, by selecting the second color signal from the color space divided on the basis of the first color signal, the second color signal becomes irregular in the color space. Even in the case of distribution, it is possible to surround the first color signal with the second color signal without reselecting the second color signal, so that the first color signal is surrounded. It becomes possible to select the second color signal at high speed.

  According to one aspect of the present invention, when the second color signal surrounding the first color signal is selected by selecting the second color signal while rotating the coordinate axis of the color space. The number of the second color signals can be reduced as much as possible, and the interpolation calculation can be performed simply.

  According to one aspect of the present invention, the color space is divided based on the comparison result between the value of each component of the first color signal and the value of each component of the second color signal. The second color signal surrounding the color signal can be selected by a simple calculation.

Further, according to one embodiment of the present invention, it is possible to perform the interpolation calculation with high accuracy by selecting the second color signal having the shortest distance from the first color signal.
In addition, according to one aspect of the present invention, by selecting the second color signal whose distance from the first color signal is equal to or greater than a predetermined value, only the color signal within a limited narrow range is selected. It is possible to prevent this, and it is possible to eliminate missing color signals that can be generated within the color reproduction range in the color space.

  According to one aspect of the present invention, when color signals are irregularly distributed in the color space by performing color signal interpolation based on the selection result of the color signals from the divided color space. In this case, color signals necessary for interpolation can be quickly selected, and color conversion can be performed at high speed.

  Further, according to one aspect of the present invention, it is possible to regularly generate interpolation points on a color space by dividing the color space on the basis of the values of the grid points on the color space. It is possible to make the color signal distribution uniform.

  According to one aspect of the present invention, the same reference point can be set for a plurality of color signals to be interpolated by setting a point different from the color signal to be interpolated as a division reference point. This makes it possible to omit the selection of the color signal used for interpolation every time a color signal within the same range is input as an interpolation target, thereby increasing the processing speed.

  Further, according to one aspect of the present invention, it is possible to regularly generate reference points on the color space by dividing the color space on the basis of the values of the grid points on the color space, which are used for interpolation. The color signal to be selected can be regularly selected.

  Further, according to one aspect of the present invention, by changing the lattice spacing of the lattice points based on the density of the color signal, it is possible to reduce overlap of the range surrounded by the color signal selected based on the lattice point. It is possible to prevent the same interpolation point from being repeatedly generated.

  According to one aspect of the present invention, the color space is divided on the basis of the color signal distributed in the color space, so that the range surrounded by the selected color signal is set on the color space without a gap. This makes it possible to eliminate missing color signals that can be generated within the color reproduction range in the color space.

  Further, according to one aspect of the present invention, the interpolation point closest to the point to be converted is selected from the interpolation points generated using the set weighting coefficient, and used when obtaining the selected interpolation point. By performing color conversion using the weighting factors, even when color signals are irregularly distributed in the color space, the number of points used for n-dimensional interpolation such as tetrahedral interpolation is reduced to n + 1. It is not necessary to limit, and interpolation points can be generated using an interpolation method that is not easily affected by noise, such as 8-point interpolation.

  In addition, according to one aspect of the present invention, selecting a color signal from the color space divided by the reference point prevents the selection of the color signal surrounding the reference point from failing, so that the selected color Interpolation points can be efficiently generated within the signal range.

  Further, according to one aspect of the present invention, by setting a volume when a cube is divided at a predetermined interval as a weighting factor at the time of interpolation, even when color signals are irregularly distributed, Interpolation points can be generated by interpolation, and an interpolation method that is less susceptible to noise can be provided.

  Further, according to one aspect of the present invention, the range surrounded by the selected color signal is distorted by changing the interval at which the cube is divided based on the distance between the selected color signals. Even in such a case, since the interpolation points can be generated uniformly, the color signal can be interpolated in a form adapted to human visual characteristics.

  Further, according to one aspect of the present invention, when a plurality of points to be converted are surrounded by the same color signal, by selecting collectively each weighting factor for the plurality of points to be converted, There is no need to repeatedly select a color signal surrounding a point to be converted, and color conversion can be performed efficiently.

  Further, according to one aspect of the present invention, even when color signals are transmitted and received between devices having different color reproducibility by converting the color signals of the device-dependent color space into color signals of an independent color space, It becomes possible to match color reproducibility between devices.

  Further, according to one aspect of the present invention, the color signal in the device-dependent color space is converted by converting the color signal in the CMY space, the CMYK space, or the RGB space into the color signal in the L * a * b * space or the XYZ space. It is possible to convert the color signal into an independent color space.

  Further, according to one aspect of the present invention, in the case where the color signal is irregularly distributed in the color space by extrapolating the color signal within the range surrounded by the color signal distributed in the color space. In addition, it is possible to generate a new color signal outside the range surrounded by the color signals distributed in the color space.

  Further, according to one aspect of the present invention, it is possible to generate interpolation points at high speed even when the color signals are irregularly distributed by selecting the color signals from the divided color space. Therefore, extrapolation points can be generated from interpolation points at high speed, and new color signals can be efficiently generated outside the range surrounded by color signals distributed in the color space. .

  Further, according to one aspect of the present invention, a color space in which color signals are irregularly distributed is divided, and a color signal is selected from the divided color space, thereby selecting a color signal to be used for the interpolation calculation. It is possible to convert an irregular table into a rule table without failure.

  Further, according to one aspect of the present invention, the color space is divided on the basis of the color signals registered in the color conversion table, so that the range surrounded by the color signals selected from the divided color spaces is gapd. Therefore, it is possible to prevent the loss of the color signal range registered in the color conversion table. In addition, according to one aspect of the present invention, by selecting a color signal by dividing a color space on the basis of a grid point, the interpolation point can be selected without failing to select a color signal used for the interpolation calculation. It is possible to generate the data at intervals, and it is possible to efficiently convert the irregular table into a rule table.

  In addition, according to one aspect of the present invention, the overlap of the range surrounded by the same color signal is reduced by using a reference point that divides the color space by thinning out the grid points registered in the color conversion table. Therefore, it becomes possible to efficiently convert the irregular table into the rule table.

  According to one aspect of the present invention, in the step of obtaining the second correspondence relationship, a volume when the cube is divided at a predetermined interval is set as a weighting factor for the selected first color signal. A step of generating an interpolation point within a range surrounded by the first color signal based on the weighting factor, and a range surrounded by the first color signal among the set weighting factors Selecting a weighting factor of an interpolation point closest to the third color signal, and calculating the fourth color signal by applying the selected weighting factor to the second color signal. I have.

  As a result, the interpolation point closest to the point to be registered in the color conversion table is selected from the interpolation points generated using the volume when the cube is divided at a predetermined interval as the weighting coefficient, and the selected interpolation point is selected. By performing color conversion using the weighting factor used in determining the color, it is possible to perform color conversion by 8-point interpolation on the color signal registered in the irregular table. Can be accurately converted to

  In addition, according to one aspect of the present invention, by performing linear calculation using two points in the vicinity of the extrapolation point, color conversion is also performed outside the range surrounded by the color signal registered in the color conversion table. Can be performed at high speed and with high accuracy.

Embodiments of the present invention will be described below with reference to the drawings.
FIG. 1 is a block diagram showing the configuration of a color signal selection apparatus according to an embodiment of the present invention.
In FIG. 1, a color space dividing unit 1 divides a color space to which the first color signal belongs with reference to the input first color signal. The color signal selection unit 2 selects a second color signal distributed in the color space from the color space divided by the color space division unit 1.

  This makes it possible to reliably surround the first color signal with the second color signal, and the first color signal can be obtained even when the second color signal is irregularly distributed in the color space. Since the selection of the color signal that does not surround the signal is prevented, it is possible to eliminate the re-selection of the color signal.

In this way, by dividing the color space into regions and selecting color signals from some of these regions, it is possible to prevent repeated data selection and to select color signals at high speed.
FIG. 2 is a diagram showing a color signal selection method according to the first embodiment of the present invention on a two-dimensional color space. In the color signal selection method according to the first embodiment, the second color signal is selected based on the magnitude relationship between the value of each component of the first color signal and the value of each component of the second color signal. I am doing so.

  In FIG. 2, it is assumed that color signals registered in the color conversion table are distributed at points P1 to P20 on the color space. It is assumed that the color signal of the point P on the color space is input as an interpolation target. Here, since the color signal of the point P is not registered in the color conversion table, four points P7, P9, P14, and P17 surrounding the point P are selected from P1 to P20 distributed in the color space. select. Then, the color signal of the point P is interpolated by performing a weight calculation using the color signals of the four selected points P7, P9, P14, and P17. In order to select the four points P7, P9, P14, and P17 surrounding the point P, the color space where P1 to P20 are distributed is divided by straight lines L1 and L2 that pass through the point P and are orthogonal to each other. By this division, four regions 1 to 4 are generated on the color space. Then, the point P7 closest to the point P is selected from the region 1, the point P9 closest to the point P is selected from the region 2, the point P14 closest to the point P is selected from the region 3, and the point P is changed from the region 4 to the point P. The closest point P17 is selected. As a result, the point P is surely surrounded by the four points P7, P9, P14, and P17, and only one color signal is selected from the four regions 1 to 4 obtained by the division, and the point P is not included in the color space. It becomes possible to take out four points P7, P9, P14, and P17 surrounding the point P from P1 to P20 distributed in the rule.

  In this way, by dividing the color space by the straight lines L1 and L2 passing through the point P and orthogonal to each other, the value of each component of the color signal at the point P is compared with the value of each component of the color signals at P1 to P20. This makes it possible to reliably select the color signals of the four points P7, P9, P14, and P17 surrounding the color signal of the point P, and to select the color signals used for interpolation at high speed with simple calculation. It becomes possible.

  In addition, by selecting the four points P7, P9, P14, and P17 that are closest to the point P from each of the divided areas 1 to 4, the color signal of the point away from the point P when performing the interpolation calculation Can be prevented, and interpolation calculation can be performed with high accuracy.

In the example of FIG. 2, since it is shown two-dimensionally, it is divided into four areas, but in three dimensions, it is divided into eight areas.
FIG. 3 is a flowchart showing a color signal selection method according to the first embodiment of the present invention.

  In FIG. 3, a color space in which color signals are distributed is divided into a plurality of regions (step S1), and color signals are selected from the divided regions (step S2). As a result, it is possible to easily find a color signal surrounding the color signal to be interpolated from irregularly distributed color signals.

FIG. 4 is a flowchart showing an area dividing method according to the first embodiment of the present invention.
In FIG. 4, first, a color signal which is a reference when dividing the color space is input (step S11). Here, the reference color signal may be a color signal to be interpolated or a grid point color signal.

Next, a plurality of areas are set in the color space based on the input color signal (step S12), and a color signal is selected from the set area (step S13).
FIG. 5 is a diagram showing a color signal selection method according to the second embodiment of the present invention on a two-dimensional color space. In the color signal selection method according to the second embodiment, the color signal surrounding the reference point can be reliably selected with as few data as possible by dividing the region after performing the rotation conversion.

  In FIG. 5, it is assumed that color signals registered in the color conversion table are distributed at points P1 to P20 on the color space. It is assumed that the color signal of the point P on the color space is input as an interpolation target. Here, since the color signal of the point P is not registered in the color conversion table, three points P4, P11, and P14 surrounding the point P are selected from P1 to P20 distributed in the color space. . Then, the color signal of the point P is interpolated by performing a weight calculation using the color signals of the three selected points P4, P11, and P14.

  In order to select three P4, P11, and P14 surrounding the point P, the point P4 closest to the point P is selected from P1 to P20 distributed on the color space. Then, the color space is divided by a straight line L1 passing through the points P and P4, and the color space is divided by a straight line L2 orthogonal to the straight line L1. By this division, four regions 1 to 4 are generated on the color space. Then, the point P11 closest to the point P from the region 3 is selected, and the point P14 closest to the point P from the region 4 is selected. As a result, the point P is surely surrounded by the three points P4, P11, and P14, and the minimum number of three points P4 that surround the point P among P1 to P20 irregularly distributed in the color space. , P11 and P14 can be taken out.

  In this way, the point closest to the reference point is first selected, rotated so that the selected point is on the coordinate axis, and then selected one by one from two opposing areas, thereby enclosing the reference point 3 points to be selected can be selected with certainty.

FIG. 6 is a flowchart showing a color signal selection method according to the second embodiment of the present invention.
In FIG. 6, first, a color signal serving as a reference when the color space is divided is input (step S21). Here, the reference color signal may be a color signal to be interpolated or a grid point color signal.

  Next, a color signal that determines the amount of rotation is selected from the color signals distributed in the color space (step S22). Here, the color signal for determining the rotation amount can be the point closest to the reference color signal.

Next, rotation calculation is performed on the color signals distributed in the color space so that the color signal that determines the rotation amount is on the coordinate axis (step S23).
Next, a plurality of areas are set in the color space with reference to the rotated color signal (step S24), and a color signal is selected from the set area (step S25).

FIG. 7 is a diagram showing a color signal selection method according to the second embodiment of the present invention on a three-dimensional color space.
In FIG. 7, four points P1 to P4 surrounding the point P in the three-dimensional space are selected. In this case, the point P1 closest to the point P is set to a negative position on the R axis, and the remaining three points P2 to P4 are selected from the region where the value on the R axis is positive. Here, the point closest to the point P in the positive region on the R axis is set as the point P2, and the point P2 is set in the negative region on the RG plane on the G axis. Then, points P3 and P4 are selected from a region where the value on the G axis is positive. Here, the point P3 is selected so that the value on the B axis is 0 or a positive region, and the point P4 is selected so that the value on the B axis is a negative region.

  That is, the value on the R axis is opposite in the point P1 and the points P2 to P4, the value on the G axis is opposite in the point P2 and the points P3 and P4, and the point P1 on the G axis The values on the B axis are opposite signs at the points P3 and P4, and the values on the B axis of the points P1 and P2 are 0.

  FIG. 8 is a diagram showing a method for selecting color signals in a three-dimensional color space according to the second embodiment of the present invention. In this example, an RGB coordinate system with the reference point P as the origin is shown, and the coordinate axes after rotation are represented by R ′, G ′, and B ′.

In FIG. 8, first, the point P1 of the color conversion table closest to the reference point P is selected.
Next, the R axis is rotated so that the point P1 has a negative value on the R axis. Note that no rotation is required when the point P1 is the origin.

Next, the point P2 of the color conversion table that is closest to the origin in the range where the R value after rotation is positive is selected.
Next, the G axis is rotated so that the point P2 is in the negative region of G on the RG plane. When the point P2 is on the R axis, rotation is not necessary.

Next, points P3 and P4 that are closest to the reference point P are selected one by one from the region where RG is positive and B is 0 or more and the region where RG is positive and B is negative.
FIG. 9 is a diagram showing a color signal selection method according to the third embodiment of the present invention on a two-dimensional color space. In the color signal selection method according to the third embodiment, by sequentially selecting the color signals registered in the color conversion table as reference points, the range surrounded by the color signal selected around the reference point is set. Therefore, it is possible to set the entire range where the registered color signals are distributed without any gaps.

  In FIG. 9, it is assumed that the color signals registered in the color conversion table are distributed at points P1 to P20 on the color space. Then, it is assumed that a reference point for selecting the points P1 to P20 distributed in the color space is set. In this case, paying attention to the points P1 to P20 distributed on the color space, the points P1 to P20 distributed on the color space are sequentially set as reference points.

For example, the point P4 distributed in the color space is set as a reference point, and the color space is divided on the basis of the point P1, thereby selecting four points P1, P2, P5, and P6 surrounding the point P4. .
Next, the selected P6 is set as a reference point, and the color space is divided using the point P6 as a reference, thereby selecting four points P2, P4, P7, and P11 surrounding the point P6.

Next, the selected P7 is set as a reference point, and the color space is divided using the point P7 as a reference, thereby selecting four points P2, P3, P6, and P9 surrounding the point P7.
By performing this reference point setting process for the points P1 to P20 distributed in the color space, the range surrounded by the points selected from the points P1 to P20 is changed to the entire range where the registered points are distributed. Can be distributed without gaps. For this reason, when a color signal with an irregular distribution is interpolated to create a color signal with a regular distribution (for example, on a grid point), a lack occurs in the range of the color signal generated in the color space. Therefore, it is possible to generate a rule table capable of performing color conversion with high accuracy.

FIG. 10 is a flowchart showing a color signal selection method according to the third embodiment of the present invention.
In FIG. 10, first, the color signals registered in the irregular table are sequentially input (step S31). Here, the order in which the color signals are input can be arbitrarily set. For example, the color signals can be input in the order stored in the irregular table.

Next, a plurality of areas are set in the color space with reference to the input color signal (step S32), and a color signal is selected from the set area (step S33).
FIG. 11 is a diagram showing a color signal selection method according to the fourth embodiment of the present invention on a two-dimensional color space. In the color signal selection method according to the fourth embodiment, a color signal is selected using a color signal registered in a newly generated color conversion table as a reference point.

  In FIG. 11, it is assumed that color signals registered in the color conversion table are distributed at points P1 to P20 on the color space. Here, the value of the color signal corresponding to the grid point on the color space is obtained by interpolation. In this case, the color space is divided using the color signal corresponding to the lattice point on the color space as a reference point, and the color signal used for interpolation is selected.

  For example, when the value of the grid point K1 is input as the reference point, the color space is divided using the grid point K1 as the reference point, and points P1, P2, P3, and P4 are selected from the divided color space, respectively. As a result, the lattice point K1 is surrounded by the points P1, P2, P3, and P4, and the value of the lattice point K1 can be obtained by performing interpolation using the values of the points P1, P2, P3, and P4. .

  When the value of the grid point K2 is input as the reference point, the color space is divided using the grid point K2 as the reference point, and points P2, P3, P4, and P5 are selected from the divided color space, respectively. As a result, the lattice point K2 is surrounded by the points P2, P3, P4, and P5, and the value of the lattice point K2 can be obtained by performing interpolation using the values of the points P2, P3, P4, and P5. .

  When the value of the grid point K3 is input as the reference point, the color space is divided using the grid point K3 as the reference point, and points P2, P3, P4, and P5 are selected from the divided color space, respectively. As a result, the lattice point K3 is surrounded by the points P2, P3, P4, and P5, and the value of the lattice point K3 can be obtained by performing interpolation using the values of the points P2, P3, P4, and P5. .

  When the value of the grid point K4 is input as the reference point, the color space is divided using the grid point K4 as the reference point, and points P4, P5, P6, and P7 are selected from the divided color space, respectively. As a result, the lattice point K4 is surrounded by the points P4, P5, P6, and P7, and the value of the lattice point K4 can be obtained by performing interpolation using the values of the points P4, P5, P6, and P7. .

  When the value of the grid point K5 is input as the reference point, the color space is divided using the grid point K5 as the reference point, and points P4, P5, P6, and P7 are selected from the divided color space, respectively. As a result, the lattice point K5 is surrounded by the points P4, P5, P6, and P7, and the value of the lattice point K5 can be obtained by performing interpolation using the values of the points P4, P5, P6, and P7. .

  In this way, by setting the reference color signal as a grid point, it is possible to reliably select the color signal surrounding the grid point, and to convert the irregular table into a rule table efficiently. Become.

FIG. 12 is a flowchart showing a color signal selection method according to the fourth embodiment of the present invention.
In FIG. 12, first, the color signals registered in the rule table are sequentially input (step S41). Here, the order in which the color signals are input can be arbitrarily set. For example, the color signals can be input in the order of the lattice numbers.

Next, a plurality of areas are set in the color space using the input color signal as a reference (step S42), and a color signal is selected from the set area (step S43).
FIG. 13 is a block diagram showing the configuration of a color signal interpolation apparatus according to an embodiment of the present invention.

In FIG. 13, the color signal input means 11 inputs a first color signal belonging to the first color space.
The color signal selection unit 12 selects a second color signal surrounding the first color signal input by the color signal input unit 11. Here, the color signal selection unit 12 divides the first color space based on the first color signal, and selects the first color signal by selecting the color signal from the divided first color space. The surrounding second color signal can be selected.

  Correspondence relationship acquisition means 13 acquires the correspondence relationship between the second color signal selected by the color signal selection means 12 and the third color signal belonging to the second color space. Here, the correspondence acquisition means 13 can acquire the correspondence between the second color signal and the third color signal by reading the data stored in the color conversion table.

  The weighting factor setting unit 14 sets a weighting factor for the second color signal selected by the color signal selection unit 12. Here, when the interpolation point generation unit 15 generates an interpolation point by 8-point interpolation, the weighting coefficient is set for each of the eight color signals selected by the color signal selection unit 12. As the weighting factors of the eight color signals, the volume when the cube is divided into eight at a specific position can be used.

When the interpolation point generation unit 15 generates an interpolation point by tetrahedral interpolation, a weighting factor is set for each of the four color signals selected by the color signal selection unit 12.
The interpolation point generation unit 15 generates an interpolation point within the range surrounded by the second color signal based on the weighting factor set by the weighting factor setting unit 14. Here, the interpolation point generating means 15 generates a plurality of interpolation points within a range surrounded by the second color signal by gradually changing the weighting coefficient set by the weighting coefficient setting means 14.

  The weighting coefficient selection unit 16 detects an interpolation point closest to the fourth color signal from the plurality of interpolation points generated by the interpolation point generation unit 15. Then, the weight coefficient of the detected interpolation point is selected from the weight coefficients set by the weight coefficient setting means 14. For this reason, even when the second color signals are irregularly distributed in the first color space, the number of second color signals used for interpolation and the weighting coefficient can be freely set. Become.

  The interpolation calculation means 17 calculates the conversion result of the fourth color signal into the second color space by applying the weight coefficient selected by the weight coefficient selection means 16 to the third color signal. For this reason, it is possible to obtain the value of the color signal in the second color space using the weighting coefficient used when obtaining the interpolation point in the first color space, and a new value in the first color space. It is possible to obtain the correspondence between the color signal given to the color signal of the second color space.

  In this way, the interpolation point closest to the point to be converted is selected from the interpolation points generated using the set weighting factor, and the color using the weighting factor used when obtaining the selected interpolation point is used. By performing the conversion, even when the color signals are irregularly distributed in the color space, it is not necessary to limit the number of points used for n-dimensional interpolation to n + 1 as in tetrahedral interpolation, and so on. Interpolation points can be generated using an interpolation method that is not easily affected by noise, such as interpolation.

  In other words, in addition to general interpolation methods such as distance interpolation, vector interpolation, and tetrahedral interpolation that can be used when color signals are irregularly distributed in the color space, sample signals and sample points are interpolated. By using an interpolation method such as 8-point interpolation that needs to exist as grid points in the two spaces to be executed, interpolation can be performed, and interpolation calculation can be performed with high accuracy.

  FIG. 14 corresponds to the input RGB value from the correspondence between the RGB value irregularly distributed in the RGB space and the L * a * b * value irregularly distributed in the L * a * b * space. It is a figure explaining the Example which calculates | requires the L * a * b * value to perform by interpolation two-dimensionally.

  In FIG. 14, it is assumed that the correspondence between the RGB values when the color chart is read by the scanner and the L * a * b * values when the color chart is measured by the colorimeter is discretely generated. . Also, the RGB values when the color chart is read by the scanner are irregularly distributed in the RGB space, and the L * a * b * values when the color chart is measured by the colorimeter are L * a * b *. Suppose that it is distributed irregularly in space. For example, point P1 in RGB space corresponds to point Q1 in L * a * b * space, point P2 in RGB space corresponds to point Q2 in L * a * b * space, and point P3 in RGB space corresponds to L *. It is assumed that the point Q4 in the a * b * space corresponds to the point P4 in the RGB space and the point P4 in the RGB space corresponds to the point Q4 in the L * a * b * space.

Here, it is assumed that a point Q in the L * a * b * space corresponding to the point P in the RGB space is obtained.
First, the points P1 to P4 surrounding the point P in the RGB space are selected. When selecting the points P1 to P4, the RGB space can be divided into four regions with the point P as a reference, and the point closest to the point P can be selected from each of the divided four regions. .

Next, a plurality of RGB values by interpolation are generated inside the area surrounded by the points P1 to p4. It is assumed that RGB values of points R1 to R12 are generated by this interpolation.
Next, a point closest to the point P is selected from the points R1 to R12 on the RGB space generated by this interpolation. It is assumed that a point R9 on the RGB space is selected by this selection.

  Next, by applying the weighting factors for the points P1 to P4 used when obtaining the point R9 to the points Q1 to Q4 on the L * a * b * space, respectively, the L * a * b * space is obtained. Find the point Q. Then, the L * a * b * value of the point Q on the L * a * b * space is output as corresponding to the RGB value of the point P on the RGB space.

  In this way, the correspondence relationship of the color signals is increased by interpolation in the irregularly distributed RGB space, and the closest one to the RGB value to be converted is found out from this. Then, by applying the weighting coefficient used for the interpolation in the RGB space to the L * a * b * value in the L * a * b * space, the irregularly distributed RGB values and the L * a From the correspondence with the * b * value, the correspondence between the input RGB value and the L * a * b * value can be obtained approximately.

FIG. 15 is a block diagram showing a system configuration of a color signal processing apparatus according to an embodiment of the present invention.
In FIG. 15, 21 is a central processing unit (CPU) that performs overall processing, 22 is a read only memory (ROM), 23 is a random access memory (RAM), 24 is an input / output interface, and 25 is based on RGB signals. A display for displaying a color image; 26, a printer for printing a color image based on the CMY signal; 27, a memory for temporarily storing data read by the scanner 28; and 28, an RGB signal by reading the color image. , A communication interface, 30 a communication network, 31 a driver for driving a storage medium, 32 a hard disk, 33 an IC memory card, 34 a magnetic tape, 35 a flexible disk, 36 a CD-ROM, DVD-ROM and other optical disks, 37 Vinegar, 38 is a keyboard.

  A program for performing color signal selection processing, a program for performing color signal interpolation processing, or the contents of a color conversion table is stored in a storage medium such as the hard disk 32, IC memory card 33, magnetic tape 34, flexible disk 35, optical disk 36, By reading the color signal selection processing program, the color signal interpolation processing program, or the contents of the color conversion table into the RAM 23, the color signal selection processing and the color signal interpolation processing can be performed. Also, the ROM 22 can store a program for performing color signal selection processing, a program for performing color signal interpolation processing, or the contents of a color conversion table.

  Furthermore, the program for performing color signal selection processing, the program for performing color signal interpolation processing, or the contents of the color conversion table can be extracted from the communication network 30 via the communication interface 29. The communication network 30 connected to the communication interface 29 includes, for example, a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, an analog telephone network, a digital telephone network (ISDN: Integrated Service Digital Network), and a PHS (Personal Handy Network). System) and satellite communication.

  The CPU 21 receives the RGB signals read by the scanner 28 when a program for performing color signal selection processing is started. When the RGB signal read by the scanner 28 is received, the RGB space is divided based on the received RGB signal. Then, RGB signals registered in the color conversion table are selected one by one from the divided RGB space. As a result, the RGB signal surrounding the received RGB signal can be selected from the RGB values registered in the color conversion table of the scanner 28.

  The CPU 21 receives the RGB signals read by the scanner 28 when a program for performing color signal interpolation processing is started. When the RGB signal read by the scanner 28 is received, the RGB signal is converted into an L * a * b * signal by referring to the color conversion table of the scanner 28. The L * a * b * signal is converted into a CMY signal by referring to the color conversion table of the printer 26 and output to the printer 26. Thereby, the color reproducibility in the scanner 28 and the color reproducibility in the printer 26 can be matched.

Next, the correspondence relationship between irregularly distributed RGB values and L * a * b * values is converted into a correspondence relationship between regularly distributed RGB values and L * a * b * values. A method will be described.
FIG. 16 is a diagram showing a color conversion table creation method according to an embodiment of the present invention on a color space. In this embodiment, the RGB values of the irregular distribution obtained by actual measurement are interpolated to generate RGB values of a regular distribution in a lattice shape, and the RGB values exceeding the range obtained by the actual measurement are obtained. Is a correspondence relationship between regularly distributed RGB values and L * a * b * values by extrapolation.

  In FIG. 16, by reading a color chart with a scanner, a distribution of RGB values corresponding to the color of the color chart is generated in the RGB space. Also, by measuring the same color chart with a colorimeter, a distribution of L * a * b * values corresponding to the color of the color chart is generated in the L * a * b * space. At this time, there is a one-to-one correspondence between RGB values distributed in the RGB space and L * a * b * values distributed in the L * a * b * space.

  Here, since the colors of the color chart are not necessarily distributed regularly, the distribution of RGB values in the RGB space and the distribution of L * a * b * values in the L * a * b * space are: It becomes irregular. As a result, a correspondence relationship between irregularly distributed RGB values and L * a * b * values is generated by actual measurement.

  Next, conversion is performed so that the RGB values are regularly distributed based on the correspondence between the irregularly distributed RGB values and the L * a * b * values. This conversion can be performed by interpolating irregularly distributed RGB values in the RGB space and obtaining L * a * b * values corresponding to lattice points in the RGB space obtained by interpolation.

This interpolation calculation can be performed, for example, by the following method.
First, an RGB value surrounding a grid point in the RGB space is selected from the measured data. Then, by sequentially setting weighting factors corresponding to the selected RGB values, a large number of interpolation points are generated in the region surrounded by the selected RGB values.

  Next, from the many generated interpolation points, the one having the closest distance to the grid point in the RGB space is detected. Then, the L * a * b * values obtained by actual measurement are interpolated using the weighting coefficients for the interpolation points detected in the RGB space. As a result, the correspondence between the RGB values of the lattice-like regular distribution and the L * a * b * values can be obtained approximately within the range of the measured RGB value distribution.

  Next, the range of the distribution of grid points in the RGB space is expanded by extrapolating the correspondence between RGB values generated using interpolation and L * a * b * values. This is because the grid points on the RGB space generated using interpolation are generated only within the range surrounded by the measured RGB signals, so the grid points on the RGB space generated using interpolation are This is because the distribution range is narrower than the measured RGB value distribution range.

  In this way, by converting the irregular table obtained by actual measurement into a rule table, it is possible to perform interpolation calculation at high speed and with high accuracy when converting RGB values to L * a * b * values. A conversion table can be generated.

FIG. 17 is a flowchart illustrating an example of a method for generating a color conversion table by interpolation.
In FIG. 17, first, a color space in which color signals are distributed is divided into a plurality of regions (step S51), and color signals are selected from the divided regions (step S52).

  Next, a color signal is newly generated by performing an interpolation operation using the selected color signal (step S53), and the newly generated color signal is registered in the color conversion table (step S54).

  In this way, by performing interpolation using the color signal selected from the divided areas, it is possible to convert the irregular table into the rule table at a high speed, and efficiently generate an easy-to-use color conversion table. It becomes possible to do.

FIG. 18 is a flowchart illustrating an example of a generation method for generating a color conversion table by extrapolation.
In FIG. 18, first, a new color signal is generated within the range of the color signal registered in the color conversion table by performing an interpolation operation using the color signal registered in the color conversion table. S61) The newly generated color signal is registered in the color conversion table (step S62).

  Next, by performing extrapolation calculation, a new color signal is generated outside the range of the color signal registered in the color conversion table (step S63), and the newly generated color signal is stored in the color conversion table. Register (step S64).

  As described above, by further extrapolating the color signals generated by the interpolation operation and increasing the color signals, the color signals to be registered in the rule table can be generated outside the range surrounded by the irregular table.

  FIG. 19 is a block diagram showing a configuration of a color conversion table generation apparatus according to an embodiment of the present invention. This color conversion table generation device enables efficient generation of a rule table from an irregular table and also prevents missing of the color signal range registered in the rule table It is.

  In FIG. 19, the scanner 43 reads the color printed on the color chart 42 and outputs the RGB value 41 a obtained as a result to the color conversion table 41. The colorimeter 44 measures the color printed on the color chart 42 and outputs the L * a * b * value 41 b obtained as a result to the color conversion table 41.

Here, since the RGB values 41a obtained from the scanner 43 and the L * a * b * values 41b obtained from the colorimeter 44 are irregularly distributed, the color conversion table 41 becomes an irregular table.
The color conversion table 49 stores the correspondence between RGB values distributed at grid points in the RGB space and L * a * b * values 49b. The range of RGB values registered in the color conversion table 49 is, for example, Assume that 0 ≦ R ≦ 256, 0 ≦ G ≦ 256, 0 ≦ B ≦ 256 corresponding to the color reproduction range of the scanner 43, and RGB values corresponding to grid points with a grid interval of 16 are registered. Therefore, the RGB value registered in the color conversion table 49 can be registered by being replaced with the RGB number 49a. The RGB number 49a is 0 ≦ R number ≦ 16, 0 ≦ G number ≦ 16, and 0 ≦ B number ≦ 16. The integer value of

Here, the RGB value is from RGB number 49a,
R value = R number × 16 (1)
G value = G number × 16 (2)
B value = B number × 16 (3)
It can ask for.

  When the RGB number 49a to be registered is given from the color conversion table 49, the selection unit 45 obtains an RGB value corresponding to the RGB number 49a according to equations (1) to (3). This RGB value corresponds to the RGB value (grid RGB value) of the grid point in the RGB space. Then, the RGB space is divided on the basis of the grid RGB value, and the RGB value 41 a surrounding the grid RGB value is selected from the RGB values 41 a registered in the color conversion table 41. Here, when the interpolation point generation by the interpolation unit 46 is performed by 8-point interpolation, eight RGB values 41a surrounding the grid RGB values are selected, and the interpolation point generation by the interpolation unit 46 is performed by tetrahedral interpolation. , Four RGB values 41a surrounding the grid RGB values are selected.

Note that the selection unit 45 may select a grid RGB value at an interval wider than the grid interval of the grid RGB value, and divide the RGB space on the basis of the selected grid RGB value.
Next, when the RGB value 41a surrounding the grid RGB value is selected, the L * a * b * value 41b corresponding to the selected RGB value 41a is read from the color conversion table 41. Then, the RGB value 41 a selected from the color conversion table 41 and the L * a * b * value 41 b read from the color conversion table 41 are output to the interpolation unit 46.

  The interpolation unit 46 sets the weighting factor for the RGB value 41a output from the selection unit 45, thereby generating an interpolation point in the region surrounded by the RGB value 41a output from the selection unit 45. Here, the interpolation unit 46 can generate an interpolation point by 8-point interpolation, tetrahedral interpolation, or the like.

  The proximity color detection unit 47 obtains a grid RGB value corresponding to the RGB number 49a output from the color conversion table 49 by using the equations (1) to (3), and the RGB value and grid of the interpolation point output from the interpolation unit 46. Compare RGB values. Then, the RGB number of the lattice point close to the RGB value of the interpolation point is detected.

  The proximity calculation unit 48 calculates the proximity between the RGB value of the interpolation point output from the interpolation unit 46 and the RGB value of the grid point detected by the proximity color detection unit 47. The degree of proximity can be defined by the square of the distance between the RGB value of the interpolation point output from the interpolation unit 46 and the RGB value of the grid point detected by the proximity color detection unit 47.

  The comparison / selection unit 50 reads the proximity 49c of the RGB number 49a of the grid point detected by the proximity color detection unit 47 from the color conversion table 49, the proximity 49c read from the color conversion table 49, and the proximity calculation unit 48. Compare with the proximity calculated in. If the proximity calculated by the proximity calculation unit 48 is greater than the proximity 49 c read from the color conversion table 49, this is transmitted to the interpolation unit 46.

  The interpolation unit 46 determines that the proximity of the interpolation points is greater than the proximity 49c registered in the color conversion table 49, or the proximity 49c is the RGB number of the grid point detected by the proximity color detection unit 47. If not registered, the RGB number 49a of the color conversion table 49 is applied to the L * a * b * value 41b corresponding to the RGB value 41a selected from the color conversion table 41 by applying the weighting coefficient of the interpolation point. L * a * b * value 49b corresponding to is calculated.

  The registration unit 51 associates the L * a * b * value 49b output from the interpolation unit 46 with the proximity output output from the comparison / selection unit 50 in correspondence with the RGB number 49a of the grid point detected by the proximity color detection unit 47. The degree 49c is registered in the color conversion table 49.

  Next, a method for creating a color conversion table for a scanner will be described more specifically using mathematical expressions. Note that the color conversion table for the scanner created here is a color conversion table used for converting RGB signals input by the scanner into L * a * b * signals. In this color conversion table, L * a * b * values corresponding to regularly distributed RGB values are registered.

  In creating this color conversion table, first, the target (on which various color charts are printed) is input with a scanner, the RGB values of the color chart are acquired, and the color chart is measured with a colorimeter. To obtain the L * a * b * value of the color chart. Here, a general IT8.7 target is used.

  What is obtained by the input by the scanner and the measurement by the colorimeter represents a correspondence between the RGB values and the L * a * b * values, and can be said to be a color conversion table. However, since the target colors are not completely regularly distributed, the RGB values and the L * a * b * values are irregularly distributed.

  The table conversion method according to the first embodiment of the present invention will be described below. The table conversion method according to the first embodiment converts an irregular table into a rule table by 8-point interpolation. The processing steps of the first embodiment are composed of three stages: “creation of color set”, “generation of rule table by interpolation”, and “addition of rule table by extrapolation”.

  In creating a color set, an irregular table color signal surrounding a grid RGB value is obtained for each grid point. Here, eight color signals are selected for each grid point. The eight color signals are hereinafter referred to as “color sets”.

In the generation of the rule table by interpolation, a large number of color signals between the color sets are generated by interpolating the color sets. Then, the color signal closest to the grid RGB value is selected from among them. By selecting a set of colors for all grid points to be registered, the L * a * b * values for each grid RGB value can be calculated. Note that using only the color signals registered in the irregular table does not always enclose all the lattice points to be registered, and therefore, the grid RGB in which L * a * b * values cannot usually be calculated. There is a value. Here, the range of RGB values to be registered in the rule table is 0 ≦ R ≦ 256, 0 ≦ G ≦ 256, 0 ≦ B ≦ 256, and grid RGB values corresponding to grid points with a grid interval of 16 are registered. Then, the grid RGB values (Rgrid, Ggrid, Bgrid) are
Rgrid = Rnum · 16 (4)
Ggrid = Gnum · 16 (5)
Bgrid = Bnum · 16 (6)
Can be calculated. Here, Rnum, Gnum, and Bnum are RGB numbers, which are integer values of 0 to 16, respectively.

In addition of the rule table by extrapolation, L * a * b * values for all the grid RGB values to be registered are calculated by extrapolating the values of the generated rule table.
Hereinafter, each step will be described in more detail.

  In creating a color set, attention is sequentially paid to lattice RGB values generated as a rule table. Then, eight color signals (target scanner input value and colorimetric value) around this grid RGB value are selected as a set of colors.

FIG. 20 is a diagram two-dimensionally showing the color signal selection method according to an embodiment of the present invention on the RGB space.
In FIG. 20, it is assumed that the RGB values registered in the irregular table are distributed at points P1 to P16 on the color space. It is assumed that the grid RGB value of the grid point K1 registered in the rule table is input as an interpolation target. Here, since the grid RGB values of the grid point K1 are not registered in the irregular table, the points P1 and P2 surrounding the grid point K1 among the RGB values of the points P1 to P16 registered in the irregular table. , P5, P10 RGB values are selected. Then, the grid RGB value of the grid point K1 is interpolated by performing a weight calculation using the RGB values of the selected points P1, P2, P5, and P10.

  To select the four points P1, P2, P5, and P10 that surround the grid point K1, the color space where the points P1 to P16 are distributed is divided by the straight lines L1 and L2 that pass through the grid point K1 and are orthogonal to each other. To do. By this division, four regions 1 to 4 are generated on the color space. Then, the point P1 closest to the lattice point K1 is selected from the region 1, the point P2 closest to the lattice point K1 is selected from the region 2, the point P10 closest to the lattice point K1 is selected from the region 3, and from the region 4 A point P5 closest to the grid point K1 is selected. As a result, the grid point K1 is surely surrounded by the four points P1, P2, P5, and P10, and only one color signal is selected from the four regions 1 to 4 obtained by the division, so that the color point is displayed on the color space. From the irregularly distributed P1 to P16, four points P1, P2, P5, and P10 surrounding the lattice point K1 can be extracted.

  When all the grid points are selected sequentially, if eight color signals surrounding the grid points cannot be selected because they are close to the boundary of the color reproduction range, a set of eight colors cannot be selected for that grid point. Shall be. For example, in FIG. 20, since no color signal is registered around the grid point with the grid number (2, 1), the color signal surrounding the grid point with the grid number (2, 1) cannot be selected.

  In this way, by sequentially selecting all the lattice points, the plane is divided into four regions with reference to the lattice points, and the color signal having the smallest distance from the lattice points is selected for each region. It is possible to reliably surround the lattice point with four points.

In FIG. 20, four color signals are selected because they are shown two-dimensionally, but eight color signals are selected in a three-dimensional space.
In the following, the color group creation algorithm will be described in order.

First, as initialization, RGB values and L * a * b * values (target colors) registered in the irregular table are set in an array.
That is, the RGB values and L * a * b * values registered in the irregular table are converted into Lin [k], ain [k], bin [k], Rin [k], Gin [k], Bin [k]. Set to. Here, the color number k is 0 ≦ k <number of colors.

Next, the color signals of the grid points in the RGB space are sequentially selected by sequentially specifying the grid numbers.
That is, the value of Rgrid, the value of Ggrid, and the value of Bgrid are sequentially set by the equations (4) to (6).

Next, the RGB space is divided into eight regions around each lattice point, and the color signal of the irregular table that is closest to the lattice point in each region is selected.
That is, for 0 ≦ i <color number, (Rin [k], Gin [k], Bin [k]) are classified into eight regions, based on the values of Rgrid, Ggrid, and Bgrid. Among the categorized regions (Rin [i], Gin [i], Bin [i]), the color number i having the smallest distance from the grid point is stored in num0 to num7.

It is as follows when expressed in mathematical formulas.
(1) Rin [i] ≦ Rgrid, Gin [i] ≦ Ggrid,
The color number i satisfying the condition of Bin [i] ≦ Bgrid is stored in num0. (2) Rin [i]> Rgrid, Gin [i] ≦ Ggrid,
Color number i satisfying the condition of Bin [i] ≦ Bgrid is stored in num1 (3) Rin [i] ≦ Rgrid, Gin [i]> Ggrid,
The color number i satisfying the condition of Bin [i] ≦ Bgrid is stored in num2. (4) Rin [i] ≦ Rgrid, Gin [i] ≦ Ggrid,
The color number i satisfying the condition of Bin [i]> Bgrid is stored in num3 (5) Rin [i]> Rgrid, Gin [i]> Ggrid,
Color number i satisfying the condition of Bin [i] ≦ Bgrid is stored in num4 (6) Rin [i] ≦ Rgrid, Gin [i]> Ggrid,
The color number i satisfying the condition of Bin [i]> Bgrid is stored in num5 (7) Rin [i]> Rgrid, Gin [i] ≦ Ggrid,
The color number i satisfying the condition of Bin [i]> Bgrid is stored in num6 (8) Rin [i]> Rgrid, Gin [i]> Ggrid,
The color number i satisfying the condition of Bin [i]> Bgrid is stored in num7. Note that a color table that cannot be set is generated only when all of the above num0 to num7 can be set, by generating a rule table by interpolation in the next step. If there is, return to grid point selection.

  FIG. 21 is a flowchart showing a method of selecting a color set according to the first embodiment of the present invention. In the flowchart of FIG. 21, the RGB value ranges registered in the rule table are 0 ≦ R ≦ 256, 0 ≦ G ≦ 256, 0 ≦ B ≦ 256, and the RGB values corresponding to the grid points with a grid interval of 16 are used. Shall be registered. Therefore, the RGB numbers (Rnum, Gnum, Bnum) are integer values in the range of 0 ≦ Rnum ≦ 16, 0 ≦ Gnum ≦ 16, and 0 ≦ Bnum ≦ 16.

  In FIG. 21, first, an input value by a scanner and a colorimetric value by a colorimeter are set in an array (step S71). Here, the color signals set in this arrangement are generally irregular, and the arrangement can be specified by designating the color number k corresponding to the target color.

  Next, the RGB number (Rnum, Gnum, Bnum) is set to 0 (step S72). Next, the RGB space is divided into eight regions around the lattice point specified by the RGB number (Rnum, Gnum, Bnum) (step S73), and the color number closest to the lattice point is determined for each divided region. k is specified (step S74). This makes it possible to select eight colors of the target that surround the colors of the grid points in the RGB space.

  Next, with respect to the lattice point specified by the RGB number (Rnum, Gnum, Bnum), it is determined whether or not the eight colors of the target surrounding the color of the lattice point have been selected (step S75). If eight colors of the target surrounding the color of the point can be selected, a rule table is generated by interpolation (step S76), and then the next grid point is selected (step S77 to step S84). . If the eight colors of the target surrounding the color of the grid point cannot be selected, the next grid point is selected without generating a rule table by interpolation for the grid point (steps S77 to S77). Step S84).

  Thereafter, each of the RGB numbers (Rnum, Gnum, Bnum) is incremented by 1 until each of the RGB numbers (Rnum, Gnum, Bnum) reaches 16 (steps S77 to S84). As a result, L * a * b * values can be registered in the rule table for the lattice points surrounded by the eight colors of the target among the 17 × 17 × 17 lattice points generated in the RGB space. .

  In the generation of the rule table by interpolation, a large number of new color signal correspondences are created by interpolating color combinations, and L corresponding to RGB values close to the grid points in the RGB space from the created color signals. * a * b * Register the value.

Since the data to be created is an L * a * b * value corresponding to the RGB number (Rnum, Gnum, Bnum) of the grid point, the actual created data format is
L [Rnum] [Gnum] [Bnum],
a [Rnum] [Gnum] [Bnum],
b [Rnum] [Gnum] [Bnum],
This is a three-dimensional array.

Hereinafter, the rule table generation algorithm by interpolation will be described in order.
First, the interval between colors created by interpolation is set. This is because when generating a large number of colors by interpolation, even if an extremely large number of interpolation points are created, many unused interpolation points are generated and are wasted. Therefore, the generation interval of colors created by interpolation is controlled. Therefore, the interpolation is performed efficiently.

  FIG. 22 is a diagram showing a method of dividing the RGB space and the L * a * b * space according to the first embodiment of the present invention. In the example of FIG. 22, the generation interval of colors created by interpolation is set so that the intervals are substantially equal in the RGB space.

  In FIG. 22, the RGB values obtained when the color chart is read by the scanner are distributed at points P1 to P9 in the RGB space, and L * a * b obtained when the color chart is measured by the colorimeter. * It is assumed that the values are distributed at points Q1 to Q9 in the L * a * b * space. Here, the points P1 to P9 correspond to the points Q1 to Q9, respectively. The points P1 to P9 are irregularly distributed in the RGB space, and the L * a * b * values corresponding to the lattice points K1 to K16 in the RGB space are used to make the irregular distribution regular. Is to be sought.

  For grid points K1 to K5, K8, K9, 16, and K12 to K16 in the RGB space, since the actual measurement points surrounding the grid points K1 to K5, K8, K9, 16, and K12 to K16 were not obtained, interpolation was performed. It is not subject to rule table generation.

  When the grid point K6 in the RGB space is a target for generating a rule table by interpolation, the RGB space is divided around the grid point K6, and the points P1, P2, P4, and P5 closest to the grid point K6 are Each is selected from the divided RGB space. When the points P1, P2, P4, and P5 are selected, interpolation points are generated in the region surrounded by the points P1, P2, P4, and P5 so as to be almost equally spaced in the RGB space.

  Then, the interpolation point R1 closest to the lattice point K6 is detected from the interpolation points generated in the region surrounded by the points P1, P2, P4, and P5. When the interpolation point R1 is detected, an interpolation point R1 is generated for the points Q1, Q2, Q4, and Q5 in the L * a * b * space corresponding to the points P1, P2, P4, and P5 in the RGB space. The interpolation point S1 in the L * a * b * space corresponding to the interpolation point R1 in the RGB space is calculated by applying the weighting factor used sometimes. Then, the L * a * b * value of the interpolation point S1 in the L * a * b * space is registered in the rule table in correspondence with the grid number of the grid point K6 in the RGB space.

  When the grid point K7 in the RGB space is a target for generating a rule table by interpolation, the RGB space is divided around the grid point K7, and the points P2, P3, P5, and P6 closest to the grid point K7 are Each is selected from the divided RGB space. When the points P2, P3, P5, and P6 are selected, interpolation points are generated in the region surrounded by the points P2, P3, P5, and P6 so as to be substantially equally spaced in the RGB space.

  Then, the interpolation point R2 closest to the grid point K7 is detected from the interpolation points generated in the region surrounded by the points P2, P3, P5, and P6. When the interpolation point R2 is detected, an interpolation point R2 is generated for the points Q2, Q3, Q5, and Q6 in the L * a * b * space corresponding to the points P2, P3, P5, and P6 in the RGB space. The interpolation point S2 on the L * a * b * space corresponding to the interpolation point R2 on the RGB space is calculated by applying the weighting factor used sometimes. Then, the L * a * b * value of the interpolation point S2 in the L * a * b * space is registered in the rule table in correspondence with the grid number of the grid point K7 in the RGB space.

  When the grid point K10 in the RGB space is a target for generating a rule table by interpolation, the RGB space is divided around the grid point K10, and the points P4, P5, P7, and P8 closest to the grid point K10 are Each is selected from the divided RGB space. When the points P4, P5, P7, and P8 are selected, interpolation points are generated in the region surrounded by the points P4, P5, P7, and P8 so as to be substantially equally spaced in the RGB space.

  Then, the interpolation point R3 closest to the lattice point K10 is detected from the interpolation points generated in the region surrounded by the points P4, P5, P7, and P8. When the interpolation point R3 is detected, an interpolation point R3 is generated for the points Q4, Q5, Q7, and Q8 in the L * a * b * space corresponding to the points P4, P5, P7, and P8 in the RGB space. The interpolation point S3 in the L * a * b * space corresponding to the interpolation point R3 in the RGB space is calculated by applying the weighting factor used sometimes. Then, the L * a * b * value of the interpolation point S3 in the L * a * b * space is registered in the rule table in correspondence with the grid number of the grid point K10 in the RGB space.

  When the grid point K11 on the RGB space is a target for generating a rule table by interpolation, the RGB space is divided around the grid point K11, and the points P5, P6, P8, and P9 closest to the grid point K11 are Each is selected from the divided RGB space. When the points P5, P6, P8, and P9 are selected, interpolation points are generated in the region surrounded by the points P5, P6, P8, and P9 so that they are almost equally spaced in the RGB space.

  Then, the interpolation point R4 closest to the grid point K11 is detected from the interpolation points generated in the region surrounded by the points P5, P6, P8, and P9. When the interpolation point R4 is detected, an interpolation point R4 is generated for the points Q5, Q6, Q8, and Q9 in the L * a * b * space corresponding to the points P5, P6, P8, and P9 in the RGB space. An interpolation point S4 in the L * a * b * space corresponding to the interpolation point R4 in the RGB space is calculated by applying the weighting factor used sometimes. Then, the L * a * b * value of the interpolation point S4 in the L * a * b * space is registered in the rule table in correspondence with the grid number of the grid point K11 in the RGB space.

  Since the interpolation points are generated within the range surrounded by the color signals selected as the color set so that the intervals are substantially equal on the RGB space, the interpolation corresponding to the RGB values is performed on the L * a * b * space. The distribution of the points is shifted to a specific area.

  FIG. 23 is a diagram showing a method of dividing the RGB space and the L * a * b * space according to the second embodiment of the present invention. In the example of FIG. 23, the generation interval of colors created by interpolation is set so that the intervals are substantially equal in the L * a * b * space.

  In FIG. 23, RGB values obtained when the color chart is read by the scanner are distributed at points P1 to P9 in the RGB space, and L * a * b obtained when the color chart is measured by the colorimeter. * It is assumed that the values are distributed at points Q1 to Q9 in the L * a * b * space. Here, the points P1 to P9 correspond to the points Q1 to Q9, respectively. The points P1 to P9 are irregularly distributed in the RGB space, and the L * a * b * values corresponding to the lattice points K1 to K16 in the RGB space are used to make the irregular distribution regular. Is to be sought.

  For grid points K1 to K5, K8, K9, 16, and K12 to K16 in the RGB space, since the actual measurement points surrounding the grid points K1 to K5, K8, K9, 16, and K12 to K16 were not obtained, interpolation was performed. It is not subject to rule table generation.

  When the grid point K6 in the RGB space is a target for generating a rule table by interpolation, the RGB space is divided around the grid point K6, and the points P1, P2, P4, and P5 closest to the grid point K6 are Each is selected from the divided RGB space. When the points P1, P2, P4, and P5 are selected, interpolation points are generated in the region surrounded by the points P1, P2, P4, and P5 so as to be almost equally spaced in the L * a * b * space. . Here, in order to generate interpolation points in the region surrounded by the points P1, P2, P4, and P5 so as to be almost equally spaced on the L * a * b * space, the L * a * b * space Based on the arrangement state of the points Q1, Q2, Q4, and Q5, a weighting factor for generating an interpolation point in the RGB space is set.

  Then, the interpolation point R1 closest to the lattice point K6 is detected from the interpolation points generated in the region surrounded by the points P1, P2, P4, and P5. When the interpolation point R1 is detected, an interpolation point R1 is generated for the points Q1, Q2, Q4, and Q5 in the L * a * b * space corresponding to the points P1, P2, P4, and P5 in the RGB space. The interpolation point S1 in the L * a * b * space corresponding to the interpolation point R1 in the RGB space is calculated by applying the weighting factor used sometimes. Then, the L * a * b * value of the interpolation point S1 in the L * a * b * space is registered in the rule table in correspondence with the grid number of the grid point K6 in the RGB space.

  When the grid point K7 in the RGB space is a target for generating a rule table by interpolation, the RGB space is divided around the grid point K7, and the points P2, P3, P5, and P6 closest to the grid point K7 are Each is selected from the divided RGB space. When the points P2, P3, P5, and P6 are selected, interpolation points are generated in the region surrounded by the points P2, P3, P5, and P6 so as to be almost equally spaced in the L * a * b * space. . Here, in order to generate interpolation points in the region surrounded by the points P2, P3, P5, and P6 so as to be almost equally spaced in the L * a * b * space, the L * a * b * space Based on the arrangement state of the points Q2, Q3, Q5, and Q6, a weighting coefficient for generating an interpolation point in the RGB space is set.

  Then, the interpolation point R2 closest to the grid point K7 is detected from the interpolation points generated in the region surrounded by the points P2, P3, P5, and P6. When the interpolation point R2 is detected, an interpolation point R2 is generated for the points Q2, Q3, Q5, and Q6 in the L * a * b * space corresponding to the points P2, P3, P5, and P6 in the RGB space. The interpolation point S2 on the L * a * b * space corresponding to the interpolation point R2 on the RGB space is calculated by applying the weighting factor used sometimes. Then, the L * a * b * value of the interpolation point S2 in the L * a * b * space is registered in the rule table in correspondence with the grid number of the grid point K7 in the RGB space.

  When the grid point K10 in the RGB space is a target for generating a rule table by interpolation, the RGB space is divided around the grid point K10, and the points P4, P5, P7, and P8 closest to the grid point K10 are Each is selected from the divided RGB space. When the points P4, P5, P7, and P8 are selected, interpolation points are generated in the region surrounded by the points P4, P5, P7, and P8 so that they are almost equally spaced in the L * a * b * space. . Here, in order to generate interpolation points in the region surrounded by the points P4, P5, P7, and P8 so as to be almost equally spaced on the L * a * b * space, the L * a * b * space Based on the arrangement state of the points Q4, Q5, Q7, and Q8, a weighting coefficient for generating interpolation points in the RGB space is set.

  Then, the interpolation point R3 closest to the lattice point K10 is detected from the interpolation points generated in the region surrounded by the points P4, P5, P7, and P8. When the interpolation point R3 is detected, an interpolation point R3 is generated for the points Q4, Q5, Q7, and Q8 in the L * a * b * space corresponding to the points P4, P5, P7, and P8 in the RGB space. The interpolation point S3 in the L * a * b * space corresponding to the interpolation point R3 in the RGB space is calculated by applying the weighting factor used sometimes. Then, the L * a * b * value of the interpolation point S3 in the L * a * b * space is registered in the rule table in correspondence with the grid number of the grid point K10 in the RGB space.

  When the grid point K11 on the RGB space is a target for generating a rule table by interpolation, the RGB space is divided around the grid point K11, and the points P5, P6, P8, and P9 closest to the grid point K11 are Each is selected from the divided RGB space. When the points P5, P6, P8, and P9 are selected, interpolation points are generated in the region surrounded by the points P5, P6, P8, and P9 so that they are almost equally spaced in the L * a * b * space. . Here, in order to generate interpolation points in the region surrounded by the points P5, P6, P8, and P9 so as to be almost equally spaced in the L * a * b * space, the L * a * b * space Based on the arrangement state of the points Q5, Q6, Q8, and Q9, a weighting coefficient for generating an interpolation point in the RGB space is set.

  Then, the interpolation point R4 closest to the grid point K11 is detected from the interpolation points generated in the region surrounded by the points P5, P6, P8, and P9. When the interpolation point R4 is detected, an interpolation point R4 is generated for the points Q5, Q6, Q8, and Q9 in the L * a * b * space corresponding to the points P5, P6, P8, and P9 in the RGB space. An interpolation point S4 in the L * a * b * space corresponding to the interpolation point R4 in the RGB space is calculated by applying the weighting factor used sometimes. Then, the L * a * b * value of the interpolation point S4 in the L * a * b * space is registered in the rule table in correspondence with the grid number of the grid point K11 in the RGB space.

  Since the interpolation points are generated within the range surrounded by the color signals selected as the color set so that they are substantially equally spaced in the L * a * b * space, L * a * b * in the RGB space. The distribution of the interpolation points corresponding to the values is shifted to a specific area.

FIG. 24 is a diagram illustrating selected points according to an embodiment of the present invention on a three-dimensional color space.
In FIG. 24, eight points P0 to P7 surrounding the point P are selected for the input point P in the three-dimensional space. Then, assuming that interpolation points are generated in the region surrounded by the eight points P0 to P7, the interpolation point generation interval is evaluated by evaluating the length of the diagonal line of the hexahedron having the points P0 to P7 as vertices. To decide.

  That is, the distance between the points P0 and P7, the distance between the points P1 and P5, the distance between the points P2 and P67, and the distance between the points P3 and P4 are represented in the three-dimensional space. Find each component above. The minimum value among the distance between the points P0 and P7, the distance between the points P1 and P5, the distance between the points P2 and P67, and the distance between the points P3 and P4. Based on the above, the generation interval of each component in the three-dimensional space is set.

Hereafter, it shows using numerical formula. Here, the generation interval of the interpolation points is set so as to be approximately equal in the L * a * b * space that is more suitable for human sense than the RGB space.
First, the Lab values of num0 to num7 set by selecting a color set can be obtained by the following equation.

L0 = Lin [num0], a0 = ain [num0],
b0 = bin [num0] (7)
L1 = Lin [num1], a1 = ain [num1],
b1 = bin [num1] (8)
L2 = Lin [num2], a2 = ain [num2],
b2 = bin [num2] (9)
L3 = Lin [num3], a3 = ain [num3],
b3 = bin [num3] (10)
L4 = Lin [num4], a4 = ain [num4],
b4 = bin [num4] (11)
L5 = Lin [num5], a5 = ain [num5],
b5 = bin [num5] (12)
L6 = Lin [num6], a6 = ain [num6],
b6 = bin [num6] (13)
L7 = Lin [num7], a7 = ain [num7],
b7 = bin [num7] (14)
Next, the minimum values of the lengths of the diagonal L component, a component, and b component of the hexahedron surrounded by the Lab values of Equations (7) to (14) can be obtained as follows.

Lint0 = (int) (W / sqrt ((L0−L7) ²
+ (A0-a7) ² + (b0-b7) ² ) +0.5)
Lint1 = (int) (W / sqrt ((L1-L5) ²
+ (A1-a5) ² + (b1-b5) ² ) +0.5)
Lint2 = (int) (W / sqrt ((L2-L6) ²
+ (A2-a6) ² + (b2-b6) ² ) +0.5)
Lint3 = (int) (W / sqrt ((L3-L4) ²
+ (A3-a4) ² + (b3-b4) ² ) +0.5)
Lint = Minimum value of Lint0 to Lint3 (15)
(However, 0 is 1)
aint0 = (int) (W / sqrt ((L0-L7) ²
+ (A0-a7) ² + (b0-b7) ² ) +0.5)
aint1 = (int) (W / sqrt ((L1-L5) ²
+ (A1-a5) ² + (b1-b5) ² ) +0.5)
aint2 = (int) (W / sqrt ((L2-L6) ²
+ (A2-a6) ² + (b2-b6) ² ) +0.5)
aint3 = (int) (W / sqrt ((L3-L4) ²
+ (A3-a4) ² + (b3-b4) ² ) +0.5)
aint = minimum value of aint0 to aint3 (however, 0 is 1) (16)
bint0 = (int) (W / sqrt ((L0-L7) ²
+ (A0-a7) ² + (b0-b7) ² ) +0.5)
bint1 = (int) (W / sqrt ((L1-L5) ²
+ (A1-a5) ² + (b1-b5) ² ) +0.5)
bint2 = (int) (W / sqrt ((L2-L6) ²
+ (A2-a6) ² + (b2-b6) ² ) +0.5)
bint3 = (int) (W / sqrt ((L3-L4) ²
+ (A3-a4) ² + (b3-b4) ² ) +0.5)
bint = minimum value of bint0 to bint3 (17)
(However, 0 is 1)
Here, W is a preset value, and is 32 here.

Then, Lint, aint, and bint obtained by the equations (15) to (17) can be used as the interpolation point generation interval.
Next, the RGB values (Rnew, Gnew, Bnew) of the new color signal are calculated by interpolation. In creating a new color signal by this interpolation, a cube whose side is W is divided into eight cubes at intervals (Lint, aint, bint) set by the equations (15) to (17). Then, an interpolation point is generated by using the volume of the cube obtained by the division as a weighting coefficient of eight color signals selected as a set of colors.

FIG. 25 is a diagram for explaining a method of calculating weighting factors used in cube interpolation according to an embodiment of the present invention.
In FIG. 25, in the range of 0 ≦ Lw ≦ W, 0 ≦ aw ≦ W, 0 ≦ bw ≦ W, inside a cube whose side is W, Lint interval for Lw, aint interval for aw, and bint for bw A point O of all combinations of intervals (Lw, aw, bw) is set, and a cube whose side is W on a plane passing through the point O is divided. At this time, the volume V (0,0,0), V (1,0,0), V (0,1,0), V (0,0,1), V (0,1) of the cube after division. , 1), V (1, 0, 1), V (1, 1, 0), V (1, 1, 1) are given by the following equations.

V (0,0,0) = (W−Lw) · (W−aw) · (W−bw)
... (18)
V (1, 0, 0) = Lw · (W−aw) · (W−bw) (19)
V (0,1,0) = (W−Lw) · aw · (W−bw) (20)
V (0,0,1) = (W−Lw) · (W−aw) bw (21)
V (0,1,1) = (W−Lw) aw · bw (22)
V (1, 0, 1) = Lw · (W−aw) bw (23)
V (1,1,0) = Lw · aw · (W−bw) (24)
V (1,1,1) = Lw · aw · bw (25)
The RGB values (R0, G0, B0) to (R7, G7, B7) of the eight color signals selected as the color set are given by the following equations.

R0 = Rin [num0], G0 = Gin [num0],
B0 = Bin [num0] (26)
R1 = Rin [num1], G1 = Gin [num1],
B1 = Bin [num1] (27)
R2 = Rin [num2], G2 = Gin [num2],
B2 = Bin [num2] (28)
R3 = Rin [num3], G3 = Gin [num3],
B3 = Bin [num3] (29)
R4 = Rin [num4], G4 = Gin [num4],
B4 = Bin [num4] (30)
R5 = Rin [num5], G5 = Gin [num5],
B5 = Bin [num5] (31)
R6 = Rin [num6], G6 = Gin [num6],
B6 = Bin [num6] (32)
R7 = Rin [num7], G7 = Gin [num7],
B7 = Bin [num7] (33)
A new color signal by interpolation is obtained by multiplying the RGB values of the eight color signals selected as the color sets of the equations (26) to (33) by the weighting factors of the equations (18) to (25), respectively. RGB values (Rnew, Gnew, Bnew) can be obtained as follows.

Rnew = (R0 · V (0,0,0) + R1 · V (1,0,0)
+ R2 · V (0,1,0) + R3 · V (0,0,1)
+ R4 · V (1,1,0) + R5 · V (0,1,1)
+ R6 · V (1, 0, 1) + R7 · V (1, 1, 1))
/ (W / W / W) (34)
Gnew = (G0 · V (0,0,0) + G1 · V (1,0,0)
+ G2 · V (0,1,0) + G3 · V (0,0,1)
+ G4 · V (1,1,0) + G5 · V (0,1,1)
+ G6 · V (1, 0, 1) + G7 · V (1, 1, 1))
/ (W / W / W) (35)
Bnew = (B0 · V (0,0,0) + B1 · V (1,0,0)
+ B2 · V (0,1,0) + B3 · V (0,0,1)
+ B4 · V (1,1,0) + B5 · V (0,1,1)
+ B6 · V (1,0,1) + B7 · V (1,1,1))
/ (W / W / W) (36)
The calculations of the equations (34) to (36) are performed in the range of 0 ≦ Lw ≦ W, 0 ≦ aw ≦ W, 0 ≦ bw ≦ W, Lint interval for Lw, aint interval for aw, and bint interval for bw. By repeating the above, a plurality of interpolation points are generated within the range surrounded by the eight color signals selected as the color set.

Next, data temporary setting is performed.
In this data temporary setting, the RGB values (Rnew, Gnew, Bnew) of the new color signal by interpolation obtained from the equations (34) to (36) and the lattice point lattice obtained from the equations (4) to (6) are used. The RGB values (Rgrid, Ggrid, Bgrid) are compared. Then, the closest color to the lattice point is detected from the new color signals generated by interpolation, and the values (Lw, aw, bw) used when generating the detected color signals are detected.

That is, the distance squared diff is calculated by the following equation.
diff = (Rgrid-Rnew) 2
+ (Ggrid-Gnew) 2 + (Bgrid-Bnew) 2
... (37)
And there is no data set at the grid point of the grid number (Rnum, Gnum, Bnum) (only the first time), or the newly calculated distance squared diff is smaller than the already set distance squared diffmin For example, data is set as follows.

diffmin = diff (38)
Lwmin = Lw (39)
awmin = aw (40)
bwmin = bw (41)
Next, data setting is performed.

  In this data setting, when the repetitive processing up to the data temporary setting is completed, L [Rnum] [Gnum] [Bnum], a [ Rnum] [Gnum] [Bnum], b [Rnum] [Gnum] [Bnum] are calculated.

That is, the reference values (Lw, aw, bw) when dividing a cube whose side is W are set as follows.
Lw = Lwmin (42)
aw = awmin (43)
bw = bwmin (44)
Then, using the values (Lw, aw, bw) set by the equations (42) to (44), the cubic volumes V (0, 0, 0), V (1, 0, 0), V (0 , 1, 0), V (0, 0, 1), V (0, 1, 1), V (1, 0, 1), V (1, 1, 0), V (1, 1, 1) Is obtained by the equations (18) to (25).

  Next, with respect to the L * a * b * values corresponding to the eight color signals selected as the color pairs of the expressions (7) to (14), the weighting coefficient obtained by the expressions (18) to (25) is used. By multiplying them, the L * a * b * values corresponding to the lattice points of the lattice numbers (Rnum, Gnum, Bnum) can be obtained by the following equations.

L [Rnum] [Gnum] [Bnum]
= (L0 · V (0,0,0) + L1 · V (1,0,0)
+ L2 · V (0,1,0) + L3 · V (0,0,1)
+ L4 · V (1,1,0) + L5 · V (0,1,1)
+ L6 · V (1,0,1) + L7 · V (1,1,1))
/ (W / W / W) (45)
a [Rnum] [Gnum] [Bnum]
= (A0 · V (0,0,0) + a1 · V (1,0,0)
+ A2 · V (0,1,0) + a3 · V (0,0,1)
+ A4 · V (1,1,0) + a5 · V (0,1,1)
+ A6 · V (1, 0, 1) + a7 · V (1, 1, 1))
/ (W / W / W)
b [Rnum] [Gnum] [Bnum] (46)
= (B0 · V (0,0,0) + b1 · V (1,0,0)
+ B2 · V (0,1,0) + b3 · V (0,0,1)
+ B4 · V (1,1,0) + b5 · V (0,1,1)
+ B6 · V (1,0,1) + b7 · V (1,1,1))
/ (W / W / W) (47)
FIG. 26 is a flowchart showing a method of generating a regular color signal by interpolation according to the first embodiment of the present invention. In the flowchart of FIG. 26, a reference value (Lw, aw, bw) for dividing a cube having 32 sides is set with Lw being a Lint interval, aw being an aint interval, and bw being a bint interval. Show.

In FIG. 26, first, the color creation intervals (Lint, aint, bint) are set by equations (15) to (17) (step S91).
Next, the reference values (Lw, aw, bw) for dividing a cube having 32 sides are set to 0 (step S92).

  Next, by dividing the cube based on the values (Lw, aw, bw), the weighting coefficients of the equations (18) to (25) are calculated. Then, by multiplying the RGB values of the eight color signals selected as color sets by the equations (26) to (33) by the weighting factors of the equations (18) to (25), a new value by interpolation is obtained. The RGB values (Rnew, Gnew, Bnew) of the color signal are calculated (step S93).

  Next, the RGB values (Rnew, Gnew, Bnew) of the new color signal obtained by the interpolation obtained in step S93 and the grid RGB values (Rgrid, Ggrid, Bgrid) of the lattice points obtained by the equations (4) to (6). The square diff of the distance between is calculated (step S94).

  Next, when there is no data set at the grid point of the grid number (Rnum, Gnum, Bnum), or the newly calculated distance squared diff is smaller than the already set distance squared diffmin (step S95), a value (Lw, aw, bw) serving as a reference when dividing the cube and the square diff of the newly calculated distance are stored (step S96).

  Hereinafter, until the reference value (Lw, aw, bw) for dividing the cube reaches 32 or more, the reference value (Lw, aw, bw) for dividing the cube is changed to the color creation interval ( By increasing the value by (Lint, aint, bint) (steps S97 to S104), the RGB values (Rnew, Gnew, Bnew) of the new color signal are calculated by interpolation.

  Next, by dividing the cube based on the values (Lw, aw, bw) stored in step S96, the weighting coefficients of equations (18) to (25) are calculated. Then, by multiplying the L * a * b * values of the eight color signals selected as the color pairs by the expressions (7) to (14) by the weighting coefficients of the expressions (18) to (25), respectively. Then, the L * a * b * value corresponding to the lattice point of the lattice number (Rnum, Gnum, Bnum) is calculated (step S105).

As described above, it is possible to generate a rule table for lattice points within the range of RGB values obtained by actual measurement.
When adding a rule table by extrapolation, if a grid point that cannot be set by generating a rule table by interpolation is detected while sequentially selecting grid points, interpolation is performed by extrapolating the color signals of the set grid points. A color signal of a grid point that could not be generated by calculation is generated. Here, by repeating the process of creating the color signal of the outer grid point for the grid point set by the interpolation calculation or extrapolation calculation, the color signal is set at the grid point of the entire color reproduction range. Can do.

  In actual processing, first, lattice points to be set are sequentially selected. If no data is set at this lattice point, it is checked whether data is set at both the adjacent lattice point and another adjacent lattice point. This investigation is performed in a predetermined order for the 26 directions. Then, the process continues until a data point set to both a grid point adjacent to a grid point for which no data is set and another grid point is detected. If these two grid points are detected, the data of the selected grid point is generated by extrapolating the two data set at this grid point.

  When the above processing is completed for all the grid points, data is set for one layer of grid points outside the set grid points. If this process is repeated many times, the grid point data can be set by any number of layers by extrapolation, and finally, the data can be set at all grid points in the RGB space.

After that, if the set L * a * b * value is outside the color reproduction range, the L * a * b * value is clipped. For example, the set L * a * b * values fall within the range of (0 ≦ L ≦ 255, −128 ≦ a ≦ 127, −128 ≦ b ≦ 127).

FIG. 27 is a diagram illustrating a method of generating RGB values of grid points by extrapolation.
In FIG. 27, assuming that the RGB values obtained by the actual measurement are distributed in the color space, the range of the RGB values of the grid points that can be generated by the interpolation calculation is inside the range surrounded by the RGB values obtained by the actual measurement. It becomes. This is because the number of color signals in the range surrounded by the RGB values obtained by actual measurement is increased by interpolation, and the color signal at the lattice point is selected from the color signals among them.

  For this reason, simply generating a rule table by increasing the number of color signals in the range surrounded by RGB values obtained by actual measurement and generating a rule table generates a rule table for the entire grid point of the device color signal range. Since it is not possible to add a color signal by extrapolation, it is possible to generate a rule table for lattice points of the entire range of the color signal of the device.

  For example, by extrapolating using two grid points K1 and K2 located outside in the range of RGB values obtained by actual measurement, the color signal of the grid point K3 outside the range of RGB values obtained by actual measurement Can be calculated. That is, a color signal symmetric with respect to the color signal corresponding to the lattice point K1 that is one inward from the lattice point K2, with the color signal corresponding to the outermost data-set lattice point K2 as the center, is the color of the lattice point K3. It can be a signal.

FIG. 28 is a diagram showing the positions of the grid points K1 to K26 adjacent to the selected grid point O in a three-dimensional space.
In FIG. 28, there are only 26 grid points K1 to K26 adjacent to the selected grid point O in the three-dimensional space. For this reason, in order to select the lattice points K1 to K26 adjacent to the selected lattice point O, it is necessary to examine 26 directions.

FIG. 29 is a diagram showing the distribution of grid points set by interpolation and grid points set by extrapolation.
In FIG. 29, assuming that the RGB values obtained by actual measurement are distributed inside the boundary A, the grid points (black circles) inside the boundary A are set by interpolation, and the data of the boundary A is set. For the outer grid point (white circle), an example is shown in which data is set by extrapolation. When data is set by extrapolation, grid points where data is not set adjacent to grid points where data has been set are detected. Then, by using data of grid points for which data has been set, data of grid points for which data has not been set is calculated.

  For example, when obtaining an L * a * b * value corresponding to a grid point P in the RGB space, a grid point P1 adjacent to the grid point P and a grid point P2 adjacent to the grid point P1 are extracted. Here, it is assumed that the L * a * b * value corresponding to the lattice point P1 and the L * a * b * value corresponding to the lattice point P2 are calculated by interpolation. Then, by using the L * a * b * value corresponding to the grid point P1 and the L * a * b * value corresponding to the grid point P2, the L * a * b * value corresponding to the grid point P is calculated. To do.

  By performing the above processing on all grid points in the RGB space, L * a * b * values can be set at grid points for one layer inside the boundary B. Further, by extrapolating using the data of the grid points inside the boundary B, L * a * b * values can be set at the grid points for one layer inside the boundary C. Furthermore, by extrapolating using the data of the grid points inside the boundary C, L * a * b * values can be set at the grid points for one layer inside the boundary D.

FIG. 30 is a diagram for explaining a method of calculating the L * a * b * values corresponding to the lattice points P in FIG. 29 by extrapolation.
In FIG. 30, a grid point P1 in the RGB space is adjacent to the grid point P, and a grid point P2 in the RGB space is adjacent to the grid point P. Further, the grid point P1 in the RGB space corresponds to the point Q1 in the L * a * b * space, and the grid point P2 in the RGB space corresponds to the point Q2 in the L * a * b * space. Furthermore, it is assumed that the L * a * b * values of the points Q1 and Q2 are calculated in the interpolation calculation. At this time, the L * a * b * value corresponding to the lattice point P can be obtained as the L * a * b * value of the point Q that is symmetric with respect to the point Q2 with respect to the point Q1.

Hereinafter, the rule table addition algorithm by extrapolation will be described in order.
First, an extrapolation set flag = 0 is set as an initial setting. This extrapolation set flag is used to determine whether data has been set for all grid points in the entire color signal range of the device. That is, only scanning all the grid points in the entire range of the device color signal can set data for only one layer outside the set grid points. In order to set data at grid points, it is necessary to repeatedly scan all the grid points in the entire range of the color signal of the device. For this reason, it is not possible to determine whether or not data has been set for all grid points in the entire range of the device color signal simply by determining whether or not all grid points in the entire range of the color signal of the device have been selected. It is.

Next, the lattice point of the lattice number (Rnum, Gnum, Bnum)
All combinations of integer values in the range of 0 ≦ Rnum <17, 0 ≦ Gnum <17, and 0 ≦ Bnum <17 are sequentially selected.

  When all the grid points have been selected, the extrapolation set flag is checked. If the extrapolation set flag = 1, the process returns to the initial setting. If the extrapolation set flag = 0, the entire process ends. To do.

  Next, only when the data is not set at the grid point of the selected grid number (Rnum, Gnum, Bnum), the subsequent processing is continued, and the data is stored at the grid point of the selected grid number (Rnum, Gnum, Bnum). Is set, the next grid point is selected.

Next, in the following order, it is examined in 26 directions whether data is set at the grid point adjacent to the grid point of the selected grid number (Rnum, Gnum, Bnum) and further one next. Then, in any of the 26 directions, at the stage where the data is set, the RGB number of the adjacent grid point is
(Rnum1, Gnum1, Bnum1),
Furthermore, the RGB number of the adjacent grid point is
(Rnum2, Gnum2, Bnum2)
And proceed to extrapolation calculation processing.

If no data set is found in any of the 26 directions, the next grid point is selected.
Here, the RGB numbers (Rnum1, Gnum1, Bnum1) of the grid points K1 to K26 adjacent to the selected grid point O and the RGB numbers (Rnum2, Gnum2, Bnum2) of the grid points adjacent to the selected grid point O are obtained. When expressed using the RGB numbers (Rnum, Gnum, Bnum) of the selected grid point O, the following equation is obtained.
1) (Rnum1, Gnum1, Bnum1)
= (Rnum + 1, Gnum, Bnum) (K1)
(Rnum2, Gnum2, Bnum2)
= (Rnum + 2, Gnum, Bnum)
2) (Rnum1, Gnum1, Bnum1)
= (Rnum-1, Gnum, Bnum) (K2)
(Rnum2, Gnum2, Bnum2)
= (Rnum-2, Gnum, Bnum)
3) (Rnum1, Gnum1, Bnum1)
= (Rnum, Gnum + 1, Bnum) (K3)
(Rnum2, Gnum2, Bnum2)
= (Rnum, Gnum + 2, Bnum)
4) (Rnum1, Gnum1, Bnum1)
= (Rnum, Gnum-1, Bnum1) (K4)
(Rnum2, Gnum2, Bnum2)
= (Rnum, Gnum-2, Bnum)
5) (Rnum1, Gnum1, Bnum1)
= (Rnum, Gnum, Bnum + 1) (K5)
(Rnum2, Gnum2, Bnum2)
= (Rnum, Gnum, Bnum + 2)
6) (Rnum1, Gnum1, Bnum1)
= (Rnum, Gnum, Bnum-1) (K6)
(Rnum2, Gnum2, Bnum2)
= (Rnum, Gnum, Bnum-2)
7) (Rnum1, Gnum1, Bnum1)
= (Rnum + 1, Gnum + 1, Bnum) (K7)
(Rnum2, Gnum2, Bnum2)
= (Rnum + 2, Gnum + 2, Bnum)
8) (Rnum1, Gnum1, Bnum1)
= (Rnum + 1, Gnum-1, Bnum) (K8)
(Rnum2, Gnum2, Bnum2)
= (Rnum + 2, Gnum-2, Bnum)
9) (Rnum1, Gnum1, Bnum1)
= (Rnum-1, Gnum + 1, Bnum) (K9)
(Rnum2, Gnum2, Bnum2)
= (Rnum-2, Gnum + 2, Bnum)
10) (Rnum1, Gnum1, Bnum1)
= (Rnum-1, Gnum-1, Bnum) (K10)
(Rnum2, Gnum2, Bnum2)
= (Rnum-2, Gnum-2, Bnum)
11) (Rnum1, Gnum1, Bnum1)
= (Rnum + 1, Gnum, Bnum + 1) (K11)
(Rnum2, Gnum2, Bnum2)
= (Rnum + 2, Gnum, Bnum + 2)
12) (Rnum1, Gnum1, Bnum1)
= (Rnum + 1, Gnum, Bnum-1) (K12)
(Rnum2, Gnum2, Bnum2)
= (Rnum-2, Gnum, Bnum-2)
13) (Rnum1, Gnum1, Bnum1)
= (Rnum-1, Gnum, Bnum + 1) (K13)
(Rnum2, Gnum2, Bnum2)
= (Rnum-2, Gnum, Bnum + 2)
14) (Rnum1, Gnum1, Bnum1)
= (Rnum-1, Gnum, Bnum-1) (K14)
(Rnum2, Gnum2, Bnum2)
= (Rnum-2, Gnum, Bnum-2)
15) (Rnum1, Gnum1, Bnum1)
= (Rnum, Gnum + 1, Bnum + 1) (K15)
(Rnum2, Gnum2, Bnum2)
= (Rnum, Gnum + 2, Bnum + 2)
16) (Rnum1, Gnum1, Bnum1)
= (Rnum, Gnum + 1, Bnum-1) (K16)
(Rnum2, Gnum2, Bnum2)
= (Rnum, Gnum + 2, Bnum-2)
17) (Rnum1, Gnum1, Bnum1)
= (Rnum, Gnum-1, Bnum + 1) (K17)
(Rnum2, Gnum2, Bnum2)
= (Rnum, Gnum-2, Bnum + 2)
18) (Rnum1, Gnum1, Bnum1)
= (Rnum, Gnum-1, Bnum-1) (K18)
(Rnum2, Gnum2, Bnum2)
= (Rnum, Gnum-2, Bnum-2)
19) (Rnum1, Gnum1, Bnum1)
= (Rnum + 1, Gnum + 1, Bnum + 1) (K19)
(Rnum2, Gnum2, Bnum2)
= (Rnum + 2, Gnum + 2, Bnum + 2)
20) (Rnum1, Gnum1, Bnum1)
= (Rnum + 1, Gnum + 1, Bnum-1) (K20)
(Rnum2, Gnum2, Bnum2)
= (Rnum + 2, Gnum + 2, Bnum-2)
21) (Rnum1, Gnum1, Bnum1)
= (Rnum + 1, Gnum-1, Bnum + 1) (K21)
(Rnum2, Gnum2, Bnum2)
= (Rnum + 2, Gnum-2, Bnum + 2)
22) (Rnum1, Gnum1, Bnum1)
= (Rnum + 1, Gnum-1, Bnum-1) (K22)
(Rnum2, Gnum2, Bnum2)
= (Rnum + 2, Gnum-2, Bnum-2)
23) (Rnum1, Gnum1, Bnum1)
= (Rnum-1, Gnum + 1, Bnum + 1) (K23)
(Rnum2, Gnum2, Bnum2)
= (Rnum-2, Gnum + 2, Bnum + 2)
24) (Rnum1, Gnum1, Bnum1)
= (Rnum-1, Gnum + 1, Bnum-1) (K24)
(Rnum2, Gnum2, Bnum2)
= (Rnum-2, Gnum + 2, Bnum-2)
25) (Rnum1, Gnum1, Bnum1)
= (Rnum-1, Gnum-1, Bnum + 1) (K25)
(Rnum2, Gnum2, Bnum2)
= (Rnum-2, Gnum-2, Bnum + 2)
26) (Rnum1, Gnum1, Bnum1)
= (Rnum-1, Gnum-1, Bnum-1) (K26)
(Rnum2, Gnum2, Bnum2)
= (Rnum-2, Gnum-2, Bnum-2)
As described above, since there are 26 directions corresponding to the next to the selected lattice point O, it is sequentially examined in the order of 1) to 26). This order is an example, and other orders may be used.

  Next, in the extrapolation calculation process, the L * a * b * values corresponding to the grid points of the RGB numbers (Rnum1, Gnum1, Bnum1) and the RGB numbers (Rnum2) are referred to by referring to the rule table generated by the interpolation. , Gnum2, Bnum2), L * a * b * values corresponding to the lattice points are obtained. Then, L * a * b * values corresponding to the grid points of the RGB numbers (Rnum2, Gnum2, Bnum2) around the L * a * b * values corresponding to the grid points of the RGB numbers (Rnum1, Gnum1, Bnum1). L * a * b * values that are symmetric with respect to are calculated by the following equation.

L [Rnum] [Gnum] [Bnum]
= L [Rnum1] [Gnum1] [Bnum1] · 2
-L [Rnum2] [Gnum2] [Bnum2] (48)
a [Rnum] [Gnum] [Bnum]
= A [Rnum1] [Gnum1] [Bnum1] · 2
-A [Rnum2] [Gnum2] [Bnum2] (49)
b [Rnum] [Gnum] [Bnum]
= B [Rnum1] [Gnum1] [Bnum1] · 2
-B [Rnum2] [Gnum2] [Bnum2] (50)
And calculated by the equations (48) to (50),
L [Rnum] [Gnum] [Bnum]
a [Rnum] [Gnum] [Bnum]
b [Rnum] [Gnum] [Bnum]
Are registered in the rule table as L * a * b * values corresponding to grid points of RGB numbers (Rnum, Gnum, Bnum). At this time, the extrapolation set flag = 1 is set.

Through the above processing, L * a * b * values for all grid points can be set.
Next, after setting the values of all grid points, the L * a * b * values are clipped by the following formula.

if 0> L then L = 0
if 100 <L then L = 100
if -128> a then a = -128
if 127 <a then a = 127
if -128> b then b = -128
if 127 <b then b = 127
With the above processing, the rule table can be generated efficiently without reselecting the color signal used for the interpolation calculation.

FIG. 31 is a flowchart showing extrapolation processing according to an embodiment of the present invention.
In FIG. 31, first, as an initial setting, an extrapolation set flag is set to 0 (step S111). In the initial state, data is set only for the lattice points within the range surrounded by the actual measurement points.

  Next, by selecting an RGB number (Rnum, Gnum, Bnum), a grid point in the RGB space is selected (step S112), and it is checked whether data is set at the selected grid point (step S113). If no data is set for the selected grid point, a data setting process is performed.

  In the data setting process, a grid point adjacent to the selected grid point and a grid point adjacent to the selected grid point are selected (step S114), and it is checked whether data of the grid point adjacent to the selected grid point and the grid point adjacent to the selected grid point has been set. (Step S115). Here, the RGB number of the adjacent grid point is (Rnum1, Gnum1, Bnum1), and the RGB number of the adjacent grid point is (Rnum2, Gnum2, Bum2).

  Then, in any of the 26 directions, when the data of the grid point adjacent to the selected grid point and the grid point adjacent to the selected grid point are set, the grid point adjacent to the selected grid point and the grid point adjacent to the selected grid point By performing extrapolation calculation processing using the above data, an L * a * b * value corresponding to the selected grid point is calculated (step S116), and an extrapolation set flag is set to 1 (step S117). ).

  On the other hand, if the data of the grid point adjacent to the selected grid point and the data of the grid point adjacent to the selected grid point are not set in all the 26 directions, all the grid points have not been selected (step S118). Returning to S112, the next grid point in the RGB space is selected.

  When the first selection of all grid points is completed and the extrapolation set flag is 1 (step S119), the process returns to step S111, and a new selection is made by performing the second selection of all grid points. The data of the grid point is set further outside the set grid point. When the above process is repeated and the setting of data for all grid points in the RGB space is completed, the extrapolation set flag is determined to be 0 in step S119, and the process ends.

  Next, a table conversion method according to the second embodiment of the present invention will be described. In the table conversion method according to the second embodiment, an irregular table is converted into a rule table by tetrahedral interpolation.

The processing steps of the second embodiment are composed of three stages: “creation of color set”, “generation of rule table by interpolation”, and “addition of rule table by extrapolation”.
In creating a color set, an irregular table color signal surrounding a grid RGB value is obtained for each grid point. Here, four color signals are selected for each grid point. These four color signals are hereinafter referred to as “color sets”.

  This set of colors is obtained by selecting four color signals (target scanner input value and colorimetric value) around this grid point from the irregular table while sequentially selecting grid RGB values to be generated as a rule table. Generated. Here, in order to efficiently select the four color signals that surround the grid points, the coordinate space is rotated according to the distribution of the color signals and the rotated coordinate axes are used as a reference instead of dividing the color space in a fixed manner. The color space is divided by the magnitude relationship of coordinate values.

In the following, the color group creation algorithm will be described in order.
First, as initialization, RGB values and L * a * b * values registered in the irregular table are set in the array.

  That is, the RGB values and L * a * b * values registered in the irregular table are converted into the arrays Lin [i], ain [i], bin [i], Rin [i], Gin [i], Bin [i ] Is set. Here, the color number i of the patch is 0 ≦ i <color number.

Next, the color signals of the grid points in the RGB space are sequentially selected by sequentially specifying the grid numbers.
That is, the value of Rgrid, the value of Ggrid, and the value of Bgrid are sequentially set by the equations (4) to (6).

Next, the RGB space is divided into four regions around each lattice point, and the color signal of the irregular table having the closest distance to the lattice point in each region is selected.
Here, the method of dividing the RGB space into four regions is performed by a rotated coordinate system. That is, the first color signal of the irregular table closest to the lattice point is selected.

Next, the R axis is rotated so that the first color signal has a negative value on the R axis.
Next, the second color signal of the irregular table closest to the origin in the range where the R value after rotation is positive is selected.

Next, the second color signal rotates the G axis so that G on the RG plane is in a negative region.
Next, a color closest to the lattice point is selected from each of a region where RG is positive and B is 0 or more, and a region where RG is positive and B is negative.

The color numbers of the four color signals selected by the above processing are stored in num1 to num4, respectively.
Only when all of the above num1 to num4 can be set, a rule table is generated by interpolation in the next step. If there is a color signal that cannot be set, the selection returns to the grid point.

  In the generation of the rule table by interpolation, a large number of new color signal correspondences are created by interpolating color combinations, and L corresponding to RGB values close to the grid points in the RGB space from the created color signals. * a * b * Register the value.

Since the data to be created is an L * a * b * value corresponding to the RGB number (Rnum, Gnum, Bnum) of the grid point, the actual created data format is
L [Rnum] [Gnum] [Bnum],
a [Rnum] [Gnum] [Bnum],
b [Rnum] [Gnum] [Bnum],
This is a three-dimensional array.

Hereinafter, the rule table generation algorithm by interpolation will be described in order. In this embodiment, priority is given to the simplicity of processing, and the color signal generation interval is fixed.
First, RGB values (Rnew, Gnew, Bnew) of a new color signal are calculated by interpolation. In the creation of new color signals by this interpolation, the weighting factors V1 to V4 for the four color signals having the color numbers num1 to num4 are created by the following procedure.

0 ≦ V1 ≦ W (51)
Sequentially set weighting coefficient V1 satisfying
0 ≦ V2 ≦ W−W1 (52)
Sequentially set the weighting coefficient V2 satisfying
0 ≦ V3 ≦ W− (V1 + V2) (53)
Sequentially set the weighting coefficient V3 satisfying
V4 = W− (V1 + V2 + V3) (54)
Set by.

Here, W is set to 32, for example.
The RGB values (R1, G1, B1) to (R4, G4, B4) of the four color signals having the color numbers num1 to num4 are given by the following equations.

R1 = Rin [num1], G1 = Gin [num1],
B1 = Bin [num1] (55)
R2 = Rin [num2], G2 = Gin [num2],
B2 = Bin [num2] (56)
R3 = Rin [num3], G3 = Gin [num3],
B3 = Bin [num3] (57)
R4 = Rin [num4], G4 = Gin [num4],
B4 = Bin [num4] (58)
Next, the RGB values of the four color signals selected as the color pairs of the expressions (55) to (58) are respectively multiplied by the weighting factors V1 to V4 set by the expressions (51) to (54). Thus, the RGB values (Rnew, Gnew, Bnew) of the new color signal by interpolation can be obtained as follows.

Rnew = (R1 * V1 + R2 * V2 + R3 * V3 + R4 * V4) / W
... (58)
Gnew = (G1 / V1 + G2 / V2 + G3 / V3 + G4 / V4) / W
... (59)
Bnew = (B1 · V1 + B2 · V2 + B3 · V3 + B4 · V4) / W
... (60)
By repeating the operations of the equations (58) to (60) for all the weighting factors V1 to V4 set by the equations (51) to (54), the color signals are surrounded by four color signals selected as a color set. A plurality of interpolation points are generated within the range.

Next, data temporary setting is performed.
In this temporary data setting, the RGB values (Rnew, Gnew, Bnew) of the new color signal by interpolation obtained from the equations (58) to (60) and the lattice point lattice obtained from the equations (4) to (6) are used. The RGB values (Rgrid, Ggrid, Bgrid) are compared. Then, a new closest color signal is detected from the new color signals by interpolation, and the weighting factors V1 to V4 used to generate the detected color signals are selected.

That is, the distance squared diff is calculated by the following equation.
diff = (Rgrid-Rnew) 2
+ (Ggrid-Gnew) 2 + (Bgrid-Bnew) 2
Then, there is no data set at the grid point of the grid number (Rnum, Gnum, Bnum) (only the first time), or the newly calculated distance squared diff is smaller than the already set distance squared diffmin. For example, data is set as follows.

diffmin = diff (61)
V1min = V1 (62)
V2min = V2 (63)
V3min = V3 (64)
V4min = V4 (65)
Next, data setting is performed.

  In this data setting, when the repetitive processing up to the data temporary setting is completed, L [Rnum] [Gnum] [Bnum], a [Rnum] are obtained by using V1min to V4min obtained by the equations (62) to (65). [Gnum] [Bnum], b [Rnum] [Gnum] [Bnum] are calculated.

  That is, the weighting factors V1 to V4 for calculating L [Rnum] [Gnum] [Bnum], a [Rnum] [Gnum] [Bnum], b [Rnum] [Gnum] [Bnum] are set as follows. To do.

V1 = V1min (66)
V2 = V2min (67)
V3 = V3min (68)
V4 = V4min (69)
The L * a * b * values (L1, a1, b1) to (L4, a4, b4) of the four color signals having the color numbers num1 to num4 are given by the following equations.

L1 = Lin [num1], a1 = ain [num1],
b1 = bin [num1] (70)
L2 = Lin [num2], a2 = ain [num2],
b2 = bin [num2] (71)
L3 = Lin [num3], a3 = ain [num3],
b3 = bin [num3] (72)
L4 = Lin [num4], a4 = ain [num4],
b4 = bin [num4] (73)
Then, by multiplying the L * a * b * values of the equations (70) to (73) by the weighting factors V1 to V4 obtained by the equations (66) to (69), the lattice numbers (Rnum, Gnum) are obtained. , Bnum), the L * a * b * value corresponding to the lattice point can be obtained by the following equation.

L [Rnum] [Gnum] [Bnum]
= (L1 ・ V1 + L2 ・ V2 + L3 ・ V3 + L4 ・ V4) / W
... (74)
a [Rnum] [Gnum] [Bnum]
= (A1, V1 + a2, V2 + a3, V3 + a4, V4) / W
... (75)
b [Rnum] [Gnum] [Bnum]
= (B1, V1 + b2, V2 + b3, V3 + b4, V4) / W
... (76)
FIG. 32 is a flowchart showing a method for generating a regular color signal by interpolation according to the second embodiment of the present invention.

In FIG. 32, first, the weighting factors V1 to V3 are set to 0 (step S121), and the weighting factor V4 is set to W− (V1 + V2 + V3) (step S122).
Next, by multiplying the RGB values of the four color signals selected as the color pairs of the equations (55) to (58) by the weighting factors V1 to V4, respectively, the RGB values of the new color signal by interpolation are obtained. (Rnew, Gnew, Bnew) is calculated (step S123).

  Next, the RGB values (Rnew, Gnew, Bnew) of the new color signal obtained by interpolation obtained in step S123, and the grid RGB values (Rgrid, Ggrid, Bgrid) of the lattice points obtained by the equations (4) to (6). A square diff of the distance between is calculated (step S124).

  Next, when there is no data set at the grid point of the grid number (Rnum, Gnum, Bnum), or the newly calculated distance squared diff is smaller than the already set distance squared diffmin (step In step S125, the weight coefficients V1 to V4 of the new color signal and the square diff of the newly calculated distance are stored (step S126).

  Hereinafter, the weighting factors V1 to V3 are increased by one each until the weighting factor V3 reaches W−V1−V2, the weighting factor V2 reaches W−V1 and the weighting factor V2 reaches W (steps S127 to S27). S134), RGB values (Rnew, Gnew, Bnew) of the new color signal are calculated by interpolation calculation.

  Next, the weighting coefficients V1 to V4 stored in step S126 are respectively multiplied with the L * a * b * values of the four color signals selected as the color set by the equations (70) to (73). Thus, the L * a * b * value corresponding to the lattice point of the lattice number (Rnum, Gnum, Bnum) is calculated (step S135). When the generation of the rule table by interpolation is completed, the rule table is added by extrapolation. The addition of the rule table by extrapolation can be performed by the same method as in the first embodiment.

  Next, a table conversion method according to the third embodiment of the present invention will be described. In the table conversion method according to the third embodiment, the irregular table is converted into the rule table by 8-point interpolation, and the reference point when dividing the RGB space is set to be different from the lattice point to be interpolated. Is possible. That is, a color signal that is a reference for selecting a set of color signals is set to a value other than the grid RGB value generated as the rule table. For example, when the grid RGB value interval is extremely small compared to the irregular table color interval, a large number of sets of the same color signal are duplicated for different grid RGB values based on the grid RGB value. Selected. Interpolation can be performed even if the same set of color signals is selected in duplicate. However, if multiple sets of the same color signal are selected in duplicate, what happens to the same set of color signals? Since the same calculation is repeatedly performed, the efficiency when the rule table is generated by interpolation may deteriorate.

  For this reason, for example, by selecting a set of colors based on an RGB value having a grid interval wider than the grid RGB value, it is possible to reduce the selection of a plurality of sets of the same color signal, and the rule by interpolation The table can be generated more efficiently.

  Further, in the case where the number of colors is increased by interpolation calculation and colors are generated for the entire color signal, if the data that are extremely close to each other are selected, the generated color signal may be lost. For example, when creating a set of irregular table data and interpolating them to create a large number of color signals distributed over the entire data distribution range of the irregular table, the range surrounded by the selected color signal There may be overlapping parts. However, if there is an unenclosed area in any set of color signals, a color signal for the unenclosed area cannot be created.

  Therefore, by providing a threshold value for selecting a color signal, extremely close data is not selected. Then, by making the surrounded range have a certain extent, it is possible to prevent the occurrence of a loss in the range surrounded by the set of color signals.

FIG. 33 is a diagram showing a method for generating a regular color signal by interpolation according to the third embodiment of the present invention on a color space.
In FIG. 33, it is assumed that color signals registered in the irregular table are distributed at points P1 to P14 on the color space. Here, the values of the color signals corresponding to the grid points K1 to K25 on the color space are obtained by interpolation. Here, it is assumed that the color space is divided using the grid points K1 to K25 on the color space as reference points, and the color signal used for interpolation is selected.

  In this case, for the lattice points K6, K7, K11, and K12, points P4, P5, P7, and P8 on the color space are selected, and generation of the rule table by interpolation is performed for each lattice point K6, K7, K11, and K12. If each is performed independently, the same interpolation calculation is repeated many times. For example, when generating RGB values (Rnew, Gnew, Bnew) of new color signals by interpolation using the equations (34) to (36) or (58) to (60), a new color by this interpolation is used. The RGB values (Rnew, Gnew, Bnew) of the signal are the same for each grid point K6, K7, K11, K12.

  Therefore, for example, with respect to the lattice points K1 to K25 to be interpolated, the reference points when dividing the color space are set at an interval twice the lattice interval of the lattice points K1 to K25, and the lattice point K1. , K3, K5, K11, K13, K15, K21, K23, and K25 are used as reference points when the color space is divided. Here, when the grid point K11 becomes a reference when dividing the color space, the points P4, P5, P7, and P8 on the color space are selected for the grid point K11.

  When points P4, P5, P7, and P8 are selected, RGB of the new color signal by interpolation is applied to the lattice points K6, K7, K11, and K12 within the range surrounded by the points P4, P5, P7, and P8. The values (Rnew, Gnew, Bnew) are generated all at once, and from the RGB values (Rnew, Gnew, Bnew) of the new color signal by the interpolation generated in batch, the respective grid points K6, K7, Those close to K11 and K12 are detected.

  As a result, it is possible to prevent the same interpolation calculation for different grid points K6, K7, K11, and K12 from being repeated many times, and it is possible to more efficiently generate a rule table by interpolation. .

  Further, when the grid point K13 becomes a reference when dividing the color space, when a point closest to the grid point K13 is selected from the divided color space, points P5, P6, P8, and P9 on the color space are selected. Is done.

  Further, when the grid point K15 becomes a reference for dividing the color space, when a point closest to the grid point K15 is selected from the divided color space, points P3, P6, P10, and P11 on the color space are selected. Is done.

  In this case, the lattice point K14 to be interpolated is surrounded by the points P5, P6, P8, P9 selected with reference to the lattice point K13 or the points P3, P6, P10, P11 selected with reference to the lattice point K15. Therefore, the interpolation calculation cannot be performed for the lattice point K14 to be interpolated. For this reason, when a point different from the grid points K1 to K25 to be interpolated is used as a reference for color space division, extremely close data is selected by providing a threshold for selecting a color signal. Do not be. For example, when the color signal is selected based on the grid point K15, the point P9 is selected instead of the point P10 located near the grid point K15.

  As a result, a region surrounded by the points P3, P6, P9, and P11 selected with the lattice point K15 as a reference is widened, and the lattice point K14 is a point P3, P6, P9, selected with the lattice point K15 as a reference. It will be surrounded by P11. As a result, even when a grid point K15 different from the grid point K14 to be interpolated is used as a reference for dividing the color space, it is possible to prevent the interpolation operation on the grid point K14 to be interpolated from becoming impossible. it can.

  The processing steps of the third embodiment include “color set creation”, “generation of rule table by interpolation (pre-processing)”, “generation of rule table by interpolation (post-processing)”, and “rule table by extrapolation” It consists of four stages of “addition of”.

  Also in the third embodiment, the rule table is generated by interpolation for each color set, but the processing to be performed for each color set is limited to the provisional data setting of the first embodiment. Then, after the processing for all the color combinations is completed, L * a * b * values are registered in the rule table all together by generating a rule table by interpolation (post-processing).

  In creating a color set, an RGB value serving as a reference when the color space is divided is set, and a color signal of an irregular table surrounding the RGB value serving as the reference is obtained for each reference RGB value. Here, eight color signals are selected for one reference RGB value. The eight color signals are hereinafter referred to as “color sets”.

  For example, with reference to an RGB value having a grid interval wider than the grid RGB value to be interpolated (for example, an interval twice the grid RGB value), a color signal surrounding the RGB value of the wider grid interval is selected. Then, the selected set of colors is interpolated to generate a large number of color signals, and a color signal close to the grid RGB value is detected from the large number of color signals generated by the interpolation. The corresponding L * a * b * value is registered in the rule table. However, the L * a * b * values are registered in a lump after the creation of all color combinations.

  It should be noted that the creation of this color set can be based on a color signal irrelevant to the grid RGB value, and there may be a gap between the regions surrounded by the selected color set. If a grid RGB enters the gap, a color signal corresponding to the grid RGB value of the gap cannot be generated. For this reason, the interval of the set of colors to be selected is slightly increased. Specifically, a color signal that is separated from the reference color signal by a certain value or more is selected so that the regions surrounded by the selected color set always overlap each other. The fixed value is preferably 0.5√3 times the interval of the reference color signal.

  By creating this color set, the color numbers i of the eight selected color signals are stored in num0 to num7. In the generation (preprocessing) of the rule table by interpolation, new color signals (Rnew, Gnew, Bnew) are obtained by interpolating using a set of colors (num0 to num7) selected based on the reference color signal. Create a correspondence for. Then, the grid RGB value closest to the newly created color signal (Rnew, Gnew, Bnew) is selected from the grid RGB values to be interpolated. Here, when the same grid RGB value is selected among a plurality of color sets (num0 to num7), a color signal (Rnew, Gnew, Bnew) having the smallest distance from the selected grid RGB value is generated. A set of colors (num0 to num7) to be selected is selected.

  When the set of colors (num0 to num7) for the grid RGB values to be interpolated is determined, the weighting factor when the color signals (Rnew, Gnew, Bnew) used to select the grid RGB values are generated is determined. . Then, L * a * b * values corresponding to the grid RGB values are generated by multiplying the L * a * b * values selected as the color pairs (num0 to num7) by this weighting factor.

  In this way, when the color signal when selecting a color set is different from the color signal to be interpolated, the color signal when selecting the color set and the color signal to be interpolated are not necessarily one-to-one. Since it does not correspond, the generation of the rule table by interpolation is skipped when the set of colors input to the rule table generation processing by interpolation is the same as that already processed. In addition, it is not possible to determine which color set is used to interpolate the grid RGB values registered in the rule table simply by setting a color signal as a reference when selecting a color set. For each generated color signal, a color set that is closest to the grid RGB is detected to select a set of colors used for interpolation of the grid RGB values.

Hereinafter, the rule table generation algorithm by interpolation will be described in order.
First, it is examined whether there is a set of the same color (num0 to num7) among already processed sets of colors. If there are exactly the same color set (num0 to num7), the rule table generation processing by interpolation is terminated, and the process returns to the creation of the color set.

Next, a color interval created by interpolation is set. This process can be performed in the same manner as the method described in the first embodiment.
Next, the RGB values (Rnew, Gnew, Bnew) of the new color signal are calculated by interpolation. This process can be performed in the same manner as the method described in the first embodiment.

Next, data temporary setting is performed.
In the temporary data setting, a grid RGB value (Rgrid, Ggrid, Bgrid) closest to the RGB value (Rnew, Gnew, Bnew) of the new color signal by interpolation obtained by the equations (34) to (36) is selected. For example, if the grid RGB values (Rgrid, Ggrid, Bgrid) are arranged at 8 intervals, the closest grid RGB values (Rgrid, Ggrid, Bgrid) can be calculated by the following formula.

Rnum = (int) ((Rnew + 4) / 8) (77)
Rgrid = Rnum · 8 (78)
Gnum = (int) ((Gnew + 4) / 8) (79)
Ggrid = Gnum · 8 (80)
Bnum = (int) ((Bnew + 4) / 8) (81)
Bgrid = Bnum · 8 (82)
Here, (int) means rounding down the decimal point.

  Next, the square of the distance between the RGB values (Rnew, Gnew, Bnew) of the new color signal by interpolation and the grid RGB values (Rgrid, Ggrid, Bgrid) selected by the equations (77) to (82) Diff is calculated by the following equation.

diff = (Rgrid−Rnew) ²
+ (Ggrid-Gnew) ² + Bgrid-Bnew) ²
If the square diff of the distance is smaller than a predetermined threshold value (for example, 2), there is no data set at the grid point of the grid number (Rnum, Gnum, Bnum) (only the first time), Alternatively, if the newly calculated distance squared diff is smaller than the already set distance squared diffmin [Rnum] [Gnum] [Bnum], data is set as follows.

diffmin [Rnum] [Gnum] [Bnum] = diff
... (83)
Lwmin [Rnum] [Gnum] [Bnum] = Lw
... (84)
awmin [Rnum] [Gnum] [Bnum] = aw
... (85)
bwmin [Rnum] [Gnum] [Bnum] = bw
... (86)
num0min [Rnum] [Gnum] [Bnum] = num0
... (87)
num1min [Rnum] [Gnum] [Bnum] = num1
... (88)
num2min [Rnum] [Gnum] [Bnum] = num2
... (89)
num3min [Rnum] [Gnum] [Bnum] = num3
... (90)
num4min [Rnum] [Gnum] [Bnum] = num4
... (91)
num5min [Rnum] [Gnum] [Bnum] = num5
... (92)
num6min [Rnum] [Gnum] [Bnum] = num6
... (93)
num7min [Rnum] [Gnum] [Bnum] = num7
... (94)
That is, in the third embodiment, in addition to the data set in the first embodiment, a set of colors (num0 to num7) is also saved, so that a set of colors (num0 to num0) used for interpolation of grid RGB values is stored. num7) can be specified. In addition, since diffmin, Lwmin, awmin, bwmin, and num0 to num7 are stored for each lattice number (Rnum, Gnum, Bnum), a three-dimensional column format is used.

  FIG. 34 is a flowchart showing a method for generating a regular color signal by interpolation according to the third embodiment of the present invention. In the flowchart of FIG. 34, a reference value (Lw, aw, bw) for dividing a cube having 32 sides is set with Lw being a Lint interval, aw being an aint interval, and bw being a bint interval. Show.

  In FIG. 34, first, it is checked whether there is a set of the same color (num0 to num7) among the set of processed colors (step S141). Then, if there is a set of exactly the same color (num0 to num7), the rule table generation processing by interpolation is terminated.

Next, the color creation intervals (Lint, aint, bint) are set according to equations (15) to (17) (step S142).
Next, the reference values (Lw, aw, bw) for dividing the cube having 32 sides are set to 0 (step S143).

  Next, by dividing the cube based on the values (Lw, aw, bw), the weighting coefficients of the equations (18) to (25) are calculated. Then, by multiplying the RGB values of the eight color signals selected as the color pairs (num0 to num7) by the equations (26) to (33), the weighting factors of the equations (18) to (25) are respectively multiplied. Then, the RGB values (Rnew, Gnew, Bnew) of the new color signal by interpolation are calculated (step S144).

  Next, the grid RGB values (Rgrid, Ggrid, Bgrid) closest to the RGB values (Rnew, Gnew, Bnew) of the new color signal by interpolation obtained by the equations (34) to (36) are expressed by (77) to ( 82) (in the case where the grid RGB values (Rgrid, Ggrid, Bgrid) are arranged at intervals of 8) (step S145).

  Next, the square diff of the distance between the RGB value (Rnew, Gnew, Bnew) of the new color signal obtained by interpolation obtained in step S144 and the grid RGB value (Rgrid, Ggrid, Bgrid) selected in step S145 is set. Calculate (step S146).

  Next, the square of the distance diff is smaller than 2, and the grid point data of the grid RGB values (Rgrid, Ggrid, Bgrid) is not set, or the square diff of the newly calculated distance is already set. When the distance is smaller than the squared diffmin (step S147), the reference value (Lw, aw, bw) for dividing the cube, the newly calculated distance squared diff, and a set of colors (num0 to num7) are stored. (Step S148).

  Hereinafter, until the reference values (Lw, aw, bw) for dividing the cube become 32 or more, the reference values (Lw, aw, bw) for dividing the cube are set to the color creation intervals ( Lattice RGB values (Rgrid, Ggrid, Bgrid) that are closest to the RGB values (Rnew, Gnew, Bnew) of the new color signal are selected by increasing (Lint, aint, bint) (steps S149 to S156).

In the generation (post-processing) of the rule table by interpolation, (84) to (94)
Lwmin [Rnum] [Gnum] [Bnum],
awmin [Rnum] [Gnum] [Bnum],
bwmin [Rnum] [Gnum] [Bnum],
num0min [Rnum] [Gnum] [Bnum]
num7min [Rnum] [Gnum] [Bnum]
L * a * b * values are calculated for the grid RGB values (Rgrid, Ggrid, Bgrid) for which the setting is completed.

That is, a set of colors (num0 to num7) used for interpolation of grid RGB values (Rgrid, Ggrid, Bgrid) is given by the following equation.
num0 = num0min [Rnum] [Gnum] [Bnum]
... (95)
num1 = num1min [Rnum] [Gnum] [Bnum]
... (96)
num2 = num2min [Rnum] [Gnum] [Bnum]
... (97)
num3 = num3min [Rnum] [Gnum] [Bnum]
... (98)
num4 = num4min [Rnum] [Gnum] [Bnum]
... (99)
num5 = num5min [Rnum] [Gnum] [Bnum]
... (100)
num6 = num6min [Rnum] [Gnum] [Bnum]
... (101)
num7 = num7min [Rnum] [Gnum] [Bnum]
... (102)
When the color set (num0-num7) is given by the equations (95) to (102), the L * a * b * values (L0, a0) of the eight color signals selected as the color set (num0-num7). , B0) to (L7, a7, b7) are given by the equations (7) to (14).

Further, values (Lw, aw, bw) for dividing the cube when generating the weighting coefficient are given by the following equations.
Lw = Lwmin [Rnum] [Gnum] [Bnum] (103)
aw = awmin [Rnum] [Gnum] [Bnum] (104)
bw = bwmin [Rnum] [Gnum] [Bnum] (105)
Then, by using the equations (103) to (105), the weighting coefficient when performing the interpolation calculation is given by the expressions (18) to (25), and the weighting coefficient obtained by the expressions (18) to (25) is used. As a result, L * a * b * values corresponding to the grid RGB values (Rgrid, Ggrid, Bgrid) can be obtained from the equations (45) to (47).

  With the above interpolation calculation, the grid RGB values in the range surrounded by the irregular table can be set in the regular table. Subsequently, as in the first embodiment, the rule table can be completed by adding the rule table by extrapolation.

  Next, a table conversion method according to the fourth embodiment of the present invention will be described. In the table conversion method according to the fourth embodiment, the irregular table is converted into the rule table by tetrahedral interpolation, and the reference point when dividing the RGB space is set to be different from the lattice point to be interpolated. Is possible.

  The processing steps of the fourth embodiment are “color set creation”, “rule table generation by interpolation (pre-processing)”, “rule table generation by interpolation (post-processing)”, and “rule table by extrapolation” It consists of four stages of “addition of”.

  In creating a color set, an RGB value serving as a reference when the color space is divided is set, and the color space is divided into eight regions around the RGB value serving as the reference. Then, three areas are selected from the eight divided areas, and the color signal closest to the reference RGB value is selected from the three selected areas. The four color signals including the reference RGB value and the selected three color signals are hereinafter referred to as “color combinations”.

  Here, the reference RGB value can be set, for example, by sequentially selecting color signals registered in the irregular table. Then, the selected set of colors is interpolated to generate a large number of color signals, and a color signal close to the grid RGB value is detected from the large number of color signals generated by the interpolation. The corresponding L * a * b * value is registered in the rule table. However, the L * a * b * values are registered in a lump after the creation of all color combinations.

FIG. 35 is a diagram showing a color signal selection method according to an embodiment of the present invention on a three-dimensional color space.
In FIG. 35, a point P that is a reference when dividing the three-dimensional space is given, and the three-dimensional space is divided into eight regions 1 to 8 around the point P. Then, the three areas adjacent to each other are selected from the eight divided areas 1 to 8, and the color signal distributed in the selected three areas is selected to be closest to the point P. . For example, regions 0, 1, 6 are selected as three regions adjacent to each other, point P0 is selected from region 0, point P1 is selected from region 1, and point P6 is selected from region 6. Note that there are 24 methods for selecting three regions adjacent to each other from the divided eight regions 1 to 8, and therefore there are 24 methods for selecting three points for the point P.

  In the following, the color group creation algorithm will be described in order. In this example, the RGB values (Rin [j], Gin [j], Bin [j]) registered in the irregular table are sequentially selected for 0 ≦ j <number of colors as the reference color signal. To do. It is assumed that the region selection method is changed in 24 ways for one reference color signal.

  First, as initialization, RGB values and L * a * b * values (target colors, 0 ≦ k <number of colors) registered in the irregular table are arrayed Lin [k], ain [k], bin. Set to [k], Rin [k], Gin [k], Bin [k].

  Next, among RGB values (Rin [k], Gin [k], Bin [k]) registered in the irregular table, RGB values (Rin [j]) serving as a reference for dividing the color space are used. , Gin [j], Bin [j]) are sequentially selected and set as follows. However, 0 ≦ j <number of colors.

Rcnet = Rin [j] (105)
Gcnet = Gin [j] (106)
Bcnet = Bin [j] (107)
Next, the RGB space is divided into eight regions around the color signal set in (105) to (107). Then, three areas are selected from the eight divided areas, and the color signal closest to the reference RGB value is selected from the three selected areas.

Specifically, for 0 ≦ i <target number of colors, the RGB space is classified into eight regions 1 to 8 as follows.
Region 0: Rin [i]> Rgrid, Gin [i] ≦ Ggrid,
Bin [i] ≦ Bgrid
However, Rin [i] = Rcent, Gin [i] = Gcent,
Excluding simultaneous establishment of three equal signs of Bin [i] = Bcent.
Region 1: Rin [i]> Rgrid, Gin [i] ≦ Ggrid,
Bin [i] ≦ Bgrid
Region 2: Rin [i] ≦ Rgrid, Gin [i]> Ggrid,
Bin [i] ≦ Bgrid
Region 3: Rin [i] ≦ Rgrid, Gin [i] ≦ Ggrid,
Bin [i]> Bgrid
Region 4: Rin [i]> Rgrid, Gin [i]> Ggrid,
Bin [i] ≦ Bgrid
Region 5: Rin [i] ≦ Rgrid, Gin [i]> Ggrid,
Bin [i]> Bgrid
Region 6: Rin [i]> Rgrid, Gin [i] ≦ Ggrid,
Bin [i]> Bgrid
Region 7: Rin [i]> Rgrid, Gin [i]> Ggrid,
Bin [i]> Bgrid
The following 24 combinations are classified into regions 1 to 8 (Rin [i], Gin [i], Bin [i]), and the reference RGB values (Rin [j], The number of the RGB value having the smallest distance from Gin [j], Bin [j]) is stored in num2 to num4. In num1, the reference RGB number is stored.

Combination 1:
num1 = j
The number of the smallest color in the areas 0, 1, and 2 with respect to the reference color is stored in num2, num3, and num4, respectively. Combination 2:
num1 = j
The number of the smallest color whose distance from the reference color is 0, 1, 3 is stored in num2, num3, and num4, respectively. Combination 3:
num1 = j
The number of the smallest color in the areas 0, 2, and 3 with respect to the reference color is stored in num2, num3, and num4, respectively. Combination 4:
num1 = j
The number of the smallest color whose distance from the reference color is in areas 0, 1, and 4 is stored in num2, num3, and num4, respectively. Combination 5:
num1 = j
The number of the smallest color in the areas 0, 1, and 6 with respect to the reference color is stored in num2, num3, and num4, respectively. Combination 6:
num1 = j
The number of the smallest color in the areas 1, 4 and 6 with respect to the reference color is stored in num2, num3 and num4, respectively. Combination 7:
num1 = j
The number of the smallest color in the areas 0, 2, and 4 with respect to the reference color is stored in num2, num3, and num4, respectively. Combination 8:
num1 = j
The number of the smallest color in the areas 0, 2, and 5 with respect to the reference color is stored in num2, num3, and num4, respectively. Combination 9:
num1 = j
Save the number of the smallest color in the areas 2, 4 and 5 to the reference color in num2, num3 and num4, respectively. Combination 10:
num1 = j
The number of the smallest color in the areas 0, 3, and 5 with respect to the reference color is stored in num2, num3, and num4, respectively. Combination 11:
num1 = j
The number of the smallest color whose distance from the reference color is 0, 3, 6 is stored in num2, num3, and num4, respectively. Combination 12:
num1 = j
The number of the smallest color in the areas 5, 3 and 6 with respect to the reference color is stored in num2, num3 and num4, respectively. Combination 13:
num1 = j
The number of the smallest color in the areas 1, 2 and 4 with respect to the reference color is stored in num2, num3, and num4, respectively. Combination 14:
num1 = j
Save the number of the smallest color in the areas 1, 4 and 7 to the reference color in num2, num3 and num4, respectively Combination 15:
num1 = j
Save the number of the smallest color in the areas 2, 4 and 7 to the reference color in num2, num3 and num4 respectively. Combination 16:
num1 = j
The number of the smallest color whose distance from the reference color is the area 2, 3, 5 is stored in num2, num3, and num4, respectively. Combination 17:
num1 = j
The number of the smallest color in the areas 2, 5, and 7 with respect to the reference color is stored in num2, num3, and num4, respectively. Combination 18:
num1 = j
The number of the smallest color in the areas 3, 5 and 7 with respect to the reference color is stored in num2, num3 and num4, respectively. Combination 19:
num1 = j
The number of the smallest color whose distance from the reference color is the area 1, 3, 6 is stored in num2, num3, and num4, respectively. Combination 20:
num1 = j
Save the number of the smallest color in the areas 1, 6 and 7 to the reference color in num2, num3 and num4 respectively. Combination 21:
num1 = j
The number of the smallest color whose distance from the reference color is in regions 3, 6 and 7 is stored in num2, num3, and num4, respectively. Combination 22:
num1 = j
The number of the smallest color whose distance from the reference color is in areas 4, 5, and 7 is stored in num2, num3, and num4, respectively. Combination 23:
num1 = j
The number of the smallest color whose distance from the reference color is the area 4, 6, 7 is stored in num2, num3, and num4, respectively. Combination 24:
num1 = j
The number of the smallest color in the areas 5, 6 and 7 with respect to the reference color is stored in num2, num3, and num4, respectively. FIG. It is a flowchart to show.

  In FIG. 36, first, an input value by the scanner and a colorimetric value by the colorimeter are set in an array (step S161). Here, the color signals set in this array are generally irregular, and the array can be specified by designating the color number j corresponding to the target color.

  Next, the color number j is set to 0 (step S162), and the RGB values (Rin [j], Gin [j], Bin [j]) specified by the color number j are selected as reference color signals. (Step S163).

Next, the combination number is set to 1 (step S164), and an area is set according to the combination number (step S165).
Next, for each set area, the color signal closest to the reference color signal is selected (step S166).

  Next, it is determined whether or not four color signals can be selected (step S167). If four color signals can be selected, a rule table is generated by interpolation (step S168). The process proceeds to S169.

  On the other hand, if the four color signals cannot be selected, it is determined whether the combination number is 24 or less (step S169). If the combination number is 24 or less, the combination number is incremented by one (step S170). Return to step S165.

  On the other hand, if the combination number exceeds 24, it is determined whether the color number j is smaller than the number of colors (step S171). If the color number j is smaller than the number of colors, the color number j is increased by one (step S171). S172), the process returns to step S163.

On the other hand, if the color number j is greater than or equal to the number of colors, the process is terminated.
When all of the above num1 to num4 are set, a rule table is generated (pre-processed) by interpolation. If there is a color signal that cannot be set, the process returns to the selection of the grid point.

  In the generation (preprocessing) of the rule table by interpolation, a set of colors (num0 to num4) selected based on the reference RGB values (Rin [j], Gin [j], Bin [j]) are used. By interpolating, a correspondence relationship between new color signals (Rnew, Gnew, Bnew) is created. The weighting coefficient at the time of interpolation calculation can be set using the equations (51) to (54), and the RGB values of the color pairs (num0 to num4) are expressed by the equations (55) to (58). The new color signal (Rnew, Gnew, Bnew) can be calculated using equations (58) to (60).

  Then, the grid RGB value closest to the newly created color signal (Rnew, Gnew, Bnew) is selected from the grid RGB values to be interpolated. Here, when the same grid RGB value is selected among a plurality of color sets (num0 to num4), a color signal (Rnew, Gnew, Bnew) having the smallest distance from the selected grid RGB value is generated. A set of colors (num0 to num4) to be selected is selected.

When the generation of the color set is completed for the color signals of all the irregular tables, the rule table is generated (post-processing) by interpolation.
In generation (post-processing) of a rule table by interpolation, when a set of colors (num0 to num4) for a grid RGB value to be interpolated is determined, the color signals (Rnew, Gnew, (Bnew) is generated. Then, L * a * b * values corresponding to the grid RGB values are generated by multiplying the L * a * b * values selected as the color pairs (num0 to num4) by this weighting factor. The weighting factor for calculating the L * a * b * value can be set using the equations (66) to (69), and each L * a * b of the color set (num0 to num4). * Values can be set using equations (70) to (73), and L * a * b * values corresponding to grid RGB values should be calculated using equations (74) to (76). Can do.

  The selection of a set of colors, generation of a rule table by interpolation (pre-processing), and generation of a rule table by interpolation (post-processing) complete setting of grid RGB values within the range surrounded by the irregular table. Subsequently, the rule table can be completed by adding the rule table by extrapolation as in the first embodiment. Note that the addition of the rule table by extrapolation can be performed in the same manner as described in the first embodiment.

  As mentioned above, although the Example of this invention was described, this invention is not limited to the Example mentioned above, Various other changes are possible within the range of the technical idea of this invention. For example, in the above-described embodiment, the method of converting the RGB value into the L * a * b * value has been described. However, the color signal of the independent color space independent of the device may be a CMY value or a CMYK value. The color signal in the device-dependent color space depending on the XYZ value may be used.

It is a block diagram which shows the structure of the color signal selection apparatus concerning one Example of this invention. It is a figure which shows the color signal selection method concerning 1st Example of this invention on a two-dimensional color space. 3 is a flowchart illustrating a color signal selection method according to the first embodiment of the present invention. It is a flowchart which shows the area division | segmentation method concerning 1st Example of this invention. It is a figure which shows the color signal selection method concerning 2nd Example of this invention on a two-dimensional color space. It is a flowchart which shows the color signal selection method concerning 2nd Example of this invention. It is a figure which shows the color signal selection method concerning 2nd Example of this invention on a three-dimensional color space. It is a figure which shows the method of selecting the color signal concerning 2nd Example of this invention on a three-dimensional color space. It is a figure which shows the color signal selection method concerning 3rd Example of this invention on a two-dimensional color space. It is a flowchart which shows the color signal selection method concerning 3rd Example of this invention. It is a figure which shows the color signal selection method concerning 4th Example of this invention on a two-dimensional color space. It is a flowchart which shows the color signal selection method concerning 4th Example of this invention. 1 is a block diagram illustrating a configuration of a color signal interpolation apparatus according to an embodiment of the present invention. It is a figure which shows the color signal interpolation method concerning one Example of this invention on color space. 1 is a block diagram showing a system configuration of a color signal processing apparatus according to an embodiment of the present invention. It is a figure which shows the color signal generation method concerning one Example of this invention on color space. 4 is a flowchart illustrating a method for generating a color conversion table according to an embodiment of the present invention. It is a flowchart which shows the extrapolation point production | generation method concerning one Example of this invention. It is a block diagram which shows the structure of the color conversion table production | generation apparatus concerning one Example of this invention. It is a figure which shows the color signal selection method concerning one Example of this invention two-dimensionally on RGB space. 3 is a flowchart showing a method for selecting a set of color signals according to the first embodiment of the present invention. It is a figure which shows the division | segmentation method of RGB space and L * a * b * space concerning 1st Example of this invention. It is a figure which shows the division | segmentation method of RGB space and L * a * b * space concerning 2nd Example of this invention. FIG. 6 is a diagram illustrating a selected point according to an embodiment of the present invention on a three-dimensional color space. It is a figure explaining the calculation method of the weighting coefficient used by the cube interpolation concerning one Example of this invention. 3 is a flowchart illustrating a method of generating a regular color signal by interpolation according to the first embodiment of the present invention. It is a figure which shows the extrapolation point production | generation method concerning one Example of this invention two-dimensionally on color space. It is a figure which shows the adjacent point on the three-dimensional space concerning one Example of this invention. It is a figure which shows the extrapolation point selection process concerning one Example of this invention two-dimensionally on RGB space. It is a figure which shows the correspondence of the RGB signal and the L * a * b * signal at the time of the extrapolation point generation concerning one Example of this invention. 5 is a flowchart illustrating a method for generating a regular color signal by extrapolation according to an embodiment of the present invention. It is a flowchart which shows the production | generation method of the regular color signal by the interpolation concerning 2nd Example of this invention. It is a figure which shows the production | generation method of the regular color signal by the interpolation concerning 3rd Example of this invention on a color space. It is a flowchart which shows the production | generation method of the regular color signal by the interpolation concerning 3rd Example of this invention. It is a figure which shows the color signal selection method concerning one Example of this invention on a three-dimensional color space. It is a flowchart which shows the selection method of the group of the color signal concerning 2nd Example of this invention. It is a flowchart which shows the conventional surrounding point selection method.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Color space division means 2 Color signal selection means 11 Color signal input means 12 Color signal selection means 13 Correspondence acquisition means 14 Weight coefficient setting means 15 Interpolation point generation means 16 Weight coefficient selection means 17 Interpolation calculation means 21 CPU
22 ROM
23 RAM
24 Input / Output Interface 25 Display 26 Printer 27 Memory 28 Scanner 29 Communication Interface 30 Communication Network 31 Driver 32 Hard Disk 33 IC Memory Card 34 Magnetic Tape 35 Flexible Disk 36 Optical Disk 37 Bus 38 Keyboard 41, 49 Color Conversion Table 41a RBG Value 41b, 49b L * a * b * value 49a RGB number 49c Proximity 42 Color chart 43 Scanner 44 Colorimeter 45 Selection unit 46 Interpolation unit 47 Proximity detection unit 48 Proximity calculation unit 50 Comparison selection unit 51 Registration unit

Claims (6)

Color space dividing means for dividing the color space into a plurality of regions using the input first color signal as a dividing boundary;
Color signal selection means for selecting a second color signal group surrounding the first color signal by selecting a color signal from the color signal group randomly distributed in each of the plurality of divided areas ;
One of the color signals is selected as one of the second color signal group from the irregularly distributed color signal group, and the irregular signal is arranged so that the signal comes to the boundary of the two or more divided areas. Rotating means for rotating the color signal group distributed in
And the color signal selection means further selects a second color signal group surrounding the first color signal by additionally selecting a color signal from a color signal group that is irregularly distributed from a region other than the region forming the boundary. selection to a color signal selecting device according to claim Rukoto. The color space dividing unit is a unit that divides the color signal value with respect to the first color signal value according to a magnitude relationship.
The color signal selection unit selects a color signal from a group of color signals that are irregularly distributed in each of the plurality of regions divided according to the magnitude relationship, thereby providing a second color signal surrounding the first color signal. 2. The color signal selection apparatus according to claim 1, wherein the color signal selection apparatus is a means for selecting a group. The color signal selection means includes
The color signal selection apparatus according to claim 1 or 2 , wherein the color signal having the shortest distance from the first color signal is selected. The color signal selection means includes
Wherein the first range distance is equal to or larger than the predetermined value of the color signal, a color signal selecting device according to any one of claims 1 to 3, distance and selects the shortest color signals. The conversion result of the color signal belonging to the first color space to the second color space is given in advance as the color signal of the second color space for the color signal group irregularly distributed in the first color space. A color signal interpolation device that generates an interpolation operation based on the correspondence relationship,
Color signal input means for inputting a first color signal belonging to the first color space;
Color space dividing means for dividing the color space into a plurality of regions using the first color signal as a boundary of division;
Color signal selection means for selecting a second color signal group, which is a color signal in a first color space surrounding the first color signal, from a plurality of divided areas;
One of the color signals is selected as one of the second color signal group from the irregularly distributed color signal group, and the irregular signal is arranged so that the signal comes to the boundary of the two or more divided areas. Rotating means for rotating the color signal group distributed in
Correspondence relationship acquisition means for determining a third color signal group that is a corresponding signal in the second color space of the second color signal group along the predetermined correspondence relationship;
Interpolation calculation means for calculating a conversion result of the first color signal into the second color space by performing an interpolation calculation on the third color signal group ;
Equipped with a,
The color signal selecting means, by adding selecting a color signal from the color signal groups randomly distributed from outside the area to make the boundary, select the second color signal group surrounding the first color signal A color signal interpolating device characterized by the above. The conversion result of the color signal belonging to the first color space into the second color space is assigned in advance to the color signal of the second color space corresponding to the color signal group irregularly distributed in the first color space. A color signal interpolation device that generates an interpolation operation based on the relationship,
Color signal input means for inputting a first color signal belonging to the first color space;
Color space dividing means for dividing the color space into a plurality of regions using the first color signal as a boundary of division;
Color signal selection means for selecting a second color signal group that is a color signal in a first color space surrounding the first color signal from a plurality of divided areas;
One of the color signals is selected as one of the second color signal group from the irregularly distributed color signal group, and the irregular signal is arranged so that the signal comes to the boundary of the two or more divided areas. Rotating means for rotating the color signal group distributed in
Correspondence relationship acquisition means for determining a third color signal group that is a corresponding signal in the second color space of the second color signal group along the predetermined correspondence relationship;
Interpolation calculation means for calculating a conversion result of an arbitrary third color signal surrounded by the second color signal group into the second color space by performing an interpolation calculation on the third color signal group and,
Equipped with a,
The color signal selecting means, by adding selecting a color signal from the color signal groups randomly distributed from outside the area to make the boundary, select the second color signal group surrounding the first color signal A color signal interpolating device characterized by the above.

Images